Composition analysis and identification of ancient glass products
Summary
For problem 1: to judge whether the cultural relics are weathered or not, now analyze the glass type, glass decoration and glass color step by step, draw a flow chart, and then get the relationship between the weathering of the glass surface and the type, decoration and color of the glass; analyze the glass The statistical law of the chemical composition content of whether there is weathering on the surface, through consulting the literature, we know that the statistical law is the frequency of random events in a large number of experiments, and it often swings around a fixed constant, that is, the expected value is used to represent the statistical law. Combining classification between type and weathering, four categories are obtained: high-potassium glass weathered, high-potassium glass unweathered, lead-barium glass weathered, and lead-barium glass unweathered. The obtained four categories of data are normalized. Find the expected value; predict the chemical composition content before weathering, use the expected values of the four data categories obtained in the previous small question to calculate the difference before and after weathering, and compare the obtained difference with the chemical composition after differentiation in Form 2 Combined, the invalid data is eliminated, and the residual value is the predicted chemical composition content.
For problem 2: analyze the classification rules of different types of glass, use MATLAB software to perform correlation analysis on the expected values of the four data categories obtained in problem 1, and obtain the relevant classification basis. The classification basis for high-potassium glass is the content of potassium oxide. The classification of lead-barium glass is based on the content of sodium oxide, lead oxide, barium oxide, and sulfur dioxide; select the appropriate chemical composition for sub-category division, and can be divided into 7 categories according to type, decoration, and surface weathering. Divided into 22 subcategories according to the color, and then according to the color to find the chemical composition of the corresponding color to get four chemical components, namely iron oxide, copper oxide, lead oxide, tin oxide, the classification results are reasonable, using a single factor Sensitivity analysis analyzes the desired results and finds that there is little change before and after the analysis, indicating that the model is reliable.
For question 3: Identify cultural relics of unknown categories and classify their types. Referring to the calculation method of statistical laws in question 1, for the 8 different cultural relics given, their chemical components are summed and normalized, and the classification rules of question 2 are used to find out the ones that have the greatest impact on high-potassium and lead-barium glass. The chemical composition is potassium oxide and lead oxide. For Table 3, compare the chemical composition ratio of potassium oxide and lead oxide. When the chemical composition ratio of potassium oxide is greater than that of lead oxide, the type of glass to be obtained is high potassium glass (If the proportion of potassium oxide = the proportion of lead oxide, it is high-potassium glass when sulfur dioxide has a value), otherwise it is lead-barium glass. The results obtained are that A1, A6, and A7 are high-potassium glasses, and A2, A3, A4, A5, and A8 are lead-barium glasses. Sensitivity analysis was carried out on the classification results , and it was found that there was little change , indicating that lead oxide (PbO) and potassium oxide (K2O) were relatively stable.
For Question 4: In order to analyze the relationship between the chemical components of different types of glass samples, according to the sub-division method in Question 2, the glass samples are divided into 7 categories and 4 kinds of chemical components are selected to calculate the expected value. The graphs of the four chemical components under different categories were synthesized. According to the definition of the association relationship, there is a strong dependence relationship between the chemical components under different categories. Analyzing its difference, using SPSS software to carry out T test on the expected value, it is found that the difference of iron oxide and copper oxide is small, and the difference of lead oxide and tin oxide is large.
Key words: normalization processing, one-way sensitivity analysis, T-test
- Question restatement
The appearance of glass had a huge impact on the lives of ancient people. Weathering is one of the most common phenomena of ancient glass . Since ancient glass has been buried underground for a long time , and the limitation of manufacturing conditions at that time will lead to different degrees of corrosion and weathering of glass. Therefore, it is of great significance to explore the chemical composition content of ancient glass to reflect the production process and process.
The main raw material for producing glass is quartz sand, and the main component is silicon dioxide. In order to lower the melting point of quartz sand, fluxes such as plant ash, natural natron, saltpeter and lead ore are added during refining. And add limestone as a stabilizer. The content of lead oxide and barium oxide in lead-barium glass is relatively high , and potassium glass is fired from substances with high potassium content . The relevant data of some ancient glass products are available. Attachment Table 1 gives the classification information of this cultural relic, and Appendix Table 2 gives the proportion of the main components of this cultural relic. The sum of the chemical composition of all data is 100%, but due to the influence of scientific and technological testing, the proportion of the sum of the chemical composition of the department is not 100%, so it is stipulated that the cumulative sum of the corresponding chemical composition is between 85% and 105% . data.
Analyze relevant data and establish mathematical modeling to solve the following problems:
For problem 1: analyze the relationship between glass surface weathering and glass type, decoration and color; according to the type of glass, analyze the statistical law of chemical composition content of whether there is weathering on the glass surface, and predict the chemical composition before weathering according to the detection data of weathering points content.
For question 2: According to the relevant data given in the attachment, analyze the classification rules of high potassium glass and lead-barium glass; for each different category, select the appropriate chemical composition to divide it into subcategories and give specific analysis methods and classification results, and analyze the rationality and sensitivity of the classification results.
For Question 3: Analyze the chemical composition of unknown glass cultural relics in Table 3 in the Annex, identify its type, and conduct sensitivity analysis on the classification results.
For question 4: For different types of glass samples, analyze the correlation between the chemical components, and compare the differences between the chemical components of different types.
- problem analysis
2.1 Question 1
In order to analyze the relationship between glass surface weathering and various influencing factors, it is necessary to classify and analyze each influencing factor in conjunction with Annex Table 1 to obtain the correlation between surface weathering and various influencing factors; The weathering conditions are classified, and for the convenience of calculation, the obtained categories are unified into units, and the discriminant conditions that can reasonably reflect the change law of the chemical composition content before and after the weathering of the glass surface are found, and finally the corresponding statistical laws are obtained; for prediction To obtain the chemical composition content before weathering, the known chemical composition content before and after weathering in Table 2 is calculated for the difference, and the chemical composition before weathering can be determined by combining the calculated difference change with the chemical composition before weathering .
2.2 Question 2
For question 2, it is necessary to analyze the classification rules of different types of glass, use the second sub-question of question 1 to analyze the different categories of glass, and simply analyze which elements have an impact on the classification of glass, and then combine MATLAB software to analyze the factors that may affect Make correlation judgments.
2.3 Question 3
Sum the chemical components of the given cultural relics of unknown categories, and respectively express the proportion of each chemical component. Since the classification law of different types of glass is determined by the relevant chemical components in question 2, combined with the different types of glass Classification rules, fill in the categories of cultural relics in the civilian category.
2.4 Question 4
Analyze the relationship between the two, according to the classification method in question 2, find out the relationship between the chemical components under different categories and analyze the correlation relationship, and use SPSS software to analyze the difference.
- model assumptions
1. Assume that other factors remain unchanged when performing univariate analysis;
2. Assuming that the cultural relics are not affected by other factors such as natural disasters, man-made disasters, etc.;
3. Assume that the cultural relics will not be oxidized by air within the experimental time to affect the experimental results;
4 Assuming that the surface of the cultural relic is cleaned and there is no stain affecting the color, the judgment of the decoration;
- Model building and solving
4.1 Question 1
Analyze the relationship between glass surface weathering and glass type, decoration and color; according to the type of glass, analyze the statistical law of chemical composition content of whether there is weathering on the glass surface, and predict the content of chemical components before weathering according to the detection data of weathering points.
4.1.1 Analysis of Problem 1
For the first small question, to judge whether the cultural relics are weathered or not, firstly, classify the type of glass, secondly, classify the ornamentation of the classified glass type, and finally, classify the color of the classified ornamentation. The relationship between whether the surface of the cultural relics is weathered and the type of glass, decoration and color can be analyzed.
For the second sub-question, in order to analyze the change law of chemical composition content before and after weathering, the change of chemical composition content is analyzed in combination with glass type and weathering status of glass surface cultural relics. It is easy to know that there are four types of combinations of glass type and glass surface weathering. They are weathered high-potassium glass, unweathered high-potassium glass, weathered lead-barium glass, and unweathered lead-barium glass. In order to unify the data indicators and facilitate the calculation, the chemical components of the four groups of data were classified and normalized, and the expected value was calculated for the processed data.
For the third question, in order to predict the chemical composition content before weathering , the glass type in Form 1 is filled in Form 2 and matched with the cultural relic sampling points in Form 2, since the glass surface has been calculated in the second question The expected value of the chemical composition content in the case of weathering or not, now calculate the difference between the expected value of different glass types before and after weathering (unweathered-weathered), combine the obtained difference with the data of the cultural relic sampling points, and eliminate The data values without corresponding elements after glass weathering and the combined data values are negative values, and the remaining value is the predicted chemical composition content before weathering.
4.1.2 Problem 1 model establishment and solution
For the first sub-question, analyze the relationship between glass surface weathering and various factors, and classify glass types, decorations, and colors in combination with Table 1 to find out the relationship between glass surface weathering and various factors. In order to reflect the correlation more intuitively, draw Figure 1 is the relationship diagram.
Figure 1 The relationship between surface weathering of cultural relics and glass type, decoration and color
It can be seen from Figure 1 that the glass type is high-potassium glass, and when the decoration is A or C, the surface of the glass is weathered regardless of the color. In the case of decoration B, there is only one color of blue-green and the glass surface is weathered; the glass type is lead-barium glass, and in the case of decoration A, the color is dark blue. The glass surface is not weathered, and the color is black and blue-green. The surface of the glass is weathered, and the color is light blue. Whether the glass surface is weathered or not cannot be judged (light blue has both weathered and unweathered parts). When the decoration is C, the color is green, the glass surface is not weathered, the color is light blue and blue-green, the glass surface is weathered, and the color is light green, dark green, purple. unweathered portion).
For the second small question, it is known from the question that the cumulative sum of the proportions of each chemical composition is an effective value between 85% and 105%. Through the analysis of Form 2 in the attachment, it is found that the proportions of each chemical composition at sampling points 15 and 17 are cumulative. and are 79.47 and 71.89 respectively, which do not meet the requirements of the topic, so the data of sampling point 15 and sampling point 17 are eliminated.
After analyzing the type of glass and whether there is weathering on the glass surface, the following four types are obtained: weathered high-potassium glass, unweathered high-potassium glass, weathered lead-barium glass, and unweathered lead-barium glass. Normalize the data listed in the above four cases [1]:
Normalization processing: It is proposed for the convenience of data processing , and the data is mapped to the range of 0 to 1 for processing, which is more convenient and fast, and belongs to the category of digital signal processing
Z is the result of normalization processing, a is the chemical composition ratio of the classified glass cultural relics, and A is the sum of the chemical element composition ratios collected at the sampling points of the cultural relics.
Using MATLAB software to normalize the data, the following table shows part of the normalized data processing
| cultural relic sampling point |
type |
surface weathering |
silica |
sodium oxide |
potassium oxide |
| 01 |
high potassium |
unweathered |
0.6858 |
0 |
0.1006 |
| 02 |
lead barium |
weathering |
0.1994 |
0 |
0 |
| 03 part 1 |
high potassium |
unweathered |
0.6380 |
0 |
0.1134 |
| 03 part 2 |
high potassium |
unweathered |
0.8170 |
0 |
0.0968 |
| 04 |
high potassium |
unweathered |
0.7102 |
0 |
0.1023 |
| 05 |
high potassium |
unweathered |
0.6012 |
0.0291 |
0.1276 |
| 06 Part 1 |
high potassium |
unweathered |
0.6623 |
0.0213 |
0.1475 |
| 06 part 2 |
high potassium |
unweathered |
0.7783 |
0 |
0 |
| 07 |
high potassium |
weathering |
0.9383 |
0 |
0 |
| 08 |
lead barium |
weathering |
0.2328 |
0 |
0 |
| 08 Severely weathered point |
lead barium |
weathering |
0.3160 |
0 |
0 |
| 09 |
high potassium |
weathering |
0.9469 |
0 |
0.0101 |
| 10 |
high potassium |
weathering |
0.9290 |
0 |
0 |
| 11 |
lead barium |
weathering |
0.2748 |
0 |
0 |
| 12 |
high potassium |
weathering |
0.9523 |
0 |
0.0059 |
( See Appendix for complete normalized data processing ) .
Table 1 Chemical composition content after normalization
After normalizing the data, it can intuitively reflect the proportion of each chemical component in the cumulative sum, and at the same time reduce the calculation error between different cultural relics.
In order to better reflect the statistical law of each component, we learned that the statistical law is that the frequency of random events in a large number of experiments often oscillates around a fixed constant, and this regularity is called statistical law. Regularity. [2] The expected value is now used to reflect the statistical regularity among the various chemical components. The figure below shows the mathematical expectation of different types of glass and whether it is weathered or not.
Table 2 Mathematical expectation under different types of glass surface with or without weathering
| surface weathering |
type |
silica |
sodium oxide |
potassium oxide |
Calcium Oxide |
| weathering |
high potassium |
94.33 |
0.00 |
0.54 |
0.87 |
| unweathered |
high potassium |
69.23 |
0.71 |
9.52 |
5.44 |
| weathering |
lead barium |
25.75 |
0.22 |
0.14 |
2.80 |
| unweathered |
lead barium |
55.83 |
1.72 |
0.23 |
1.34 |
| surface weathering |
type |
Aluminum oxide |
iron oxide |
Copper oxide |
lead oxide |
| weathering |
high potassium |
1.94 |
0.27 |
1.57 |
0.00 |
| unweathered |
high potassium |
6.74 |
1.97 |
2.50 |
0.42 |
| weathering |
lead barium |
3.06 |
0.61 |
2.33 |
44.89 |
| unweathered |
lead barium |
4.55 |
0.76 |
1.48 |
22.58 |
| surface weathering |
type |
Phosphorus pentoxide |
strontium oxide |
tin oxide |
sulfur dioxide |
| weathering |
high potassium |
0.28 |
0.00 |
0.00 |
0.00 |
| unweathered |
high potassium |
1.43 |
0.04 |
0.20 |
0.11 |
| weathering |
lead barium |
5.48 |
0.43 |
0.07 |
1.38 |
| unweathered |
lead barium |
1.10 |
0.27 |
0.05 |
0.16 |
It can be seen from Table 2 that the analysis of the expected value shows that only the content of silicon dioxide in the high-potassium glass increases before and after weathering, and the content of other chemical components decreases. The chemical composition of lead-barium glass before and after weathering is calcium oxide, copper oxide, lead oxide, phosphorus pentoxide, strontium oxide, tin oxide, sulfur dioxide, silicon dioxide, sodium oxide, potassium oxide, aluminum oxide, iron oxide content decreased.
In order to more intuitively show the statistical law of the content of each component, the chemical component content of each glass before and after weathering is drawn into a broken line statistical chart, as shown in the figure below :
Figure 2 Chemical composition content of each glass before and after weathering
For the third question, in order to predict the chemical composition content before weathering, the expected value obtained in the second question can be used for prediction. Now match the glass type in Form 1 and whether the surface is weathered or not and fill it into Form 2.
Classify and discuss the glass type and whether it is weathered or not. When the glass type is high-potassium glass, use the expected value obtained in the second small question to find the difference in the chemical composition content of the high-potassium glass before and after weathering . Similarly, you can also find The difference in chemical composition content before and after weathering of lead-barium glass was obtained . Part of the data is shown in the table below (see the appendix for complete data) :
Table 3 Differences in chemical composition content of different types of glass before and after weathering
| type |
sodium oxide |
potassium oxide |
lead oxide |
barium oxide |
sulfur dioxide |
| high potassium |
0.71 |
8.97 |
0.42 |
0.61 |
0.11 |
| lead barium |
1.5 |
0.09 |
-22.31 |
-2.87 |
-1.22 |
Adding and summing the difference obtained in the above table and Table 2, the chemical composition content before weathering can be predicted.
Combine the calculated difference with Form 2 to fill in the chemical composition content given by the cultural relic sampling points, and some results are shown in the following table ( see the appendix for complete data ) :
| cultural relic sampling point |
type |
silica |
potassium oxide |
Calcium Oxide |
Aluminum oxide |
lead oxide |
| 2 |
lead barium |
65.13 |
1.02 |
1.19 |
7.23 |
28.64 |
| 7 |
high potassium |
62.42 |
6.19 |
6.23 |
||
| 8 |
lead barium |
48.99 |
0.33 |
2.84 |
9.89 |
|
| 08 |
lead barium |
33.46 |
2.04 |
2.61 |
13.66 |
|
| 9 |
high potassium |
64.81 |
9.29 |
5.74 |
5.57 |
|
| 10 |
high potassium |
66.56 |
9.62 |
5.33 |
5.06 |
|
| 11 |
lead barium |
62.44 |
0.18 |
2.36 |
4.19 |
6.6 |
| 12 |
high potassium |
64.08 |
9.71 |
5.84 |
5.71 |
Table 4 Predicted chemical composition content before weathering
The above table shows the predicted chemical composition content before weathering. For the case where there is no relevant element data after weathering and the value is negative after data filling, in order to avoid the impact of abnormal data on the remaining chemical composition content, the abnormal data is now eliminated.
4.2 Question 2
Based on the relevant data given in the appendix, analyze the classification rules of high potassium glass and lead-barium glass; for each different category, select the appropriate chemical composition to divide it into subcategories and give specific analysis methods and classification results. And analyze the rationality and sensitivity of the classification results.
4.2.1 Analysis of Question 2
For the first small question, in order to analyze the classification rules of different types of glass, that is, to analyze the influence of color, ornamentation and different chemical components on glass classification, it can be seen from question 1 that color and ornamentation have no strong distinction for glass classification. Then analyze the classification law of glass, that is, analyze the relationship between the expected value of each chemical composition and the glass type and whether it is weathered, use MATLAB software to judge the relationship between the expected value of each chemical composition and the glass type and the weathering of the glass surface, and through the judgment can be obtained High Classification rules of potassium glass and lead-barium glass.
对于第2小问，首先先根据类型，纹饰，表面风化可分为7个类别，7个类别再根据颜色的不同分为22个亚类，然后根据颜色找到相对应颜色的化学成分得到四个化学成分分别为氧化铁(Fe2O3)，氧化铜(CuO)，氧化铅(PbO)，氧化锡(SnO2)。求22个亚类，4个化学成分的期望，最后按颜色分为8类对分类结果进行合理性分析和敏感性分析。
4.2.2 问题二模型的建立模型求解
对于第1小问，由问题1可知，纹饰、颜色对于玻璃的分类影响不是最大的，故排除对纹饰、颜色对于玻璃的分类。
对表单2文物采样点的化学成分数据进行累加求和，由题知，有效数据区间介于85%—105%。对无效数据进行剔除，剔除无效数据后，将剩余数据进行归一化处理。
对高钾玻璃、铅钡玻璃和玻璃表面有无风化为依据，可分四种类型（高钾玻璃风化、高钾玻璃未风化、铅钡玻璃风化、铅钡玻璃未风化）。
分别求各类型下的化学成分期望值，判断各化学成分的期望值与玻璃表面风化的关系，现运用MATLAB软件进行判断。假定1表示该化学成分对于高钾玻璃、铅钡玻璃的影响大，即可求出各化学成分与玻璃类别的相关性，结果如下图所示：
表 5各化学成分与不同类别玻璃的相关性
| 二氧化硅 |
氧化钠 |
氧化钾 |
氧化钙 |
氧化镁 |
氧化铝 |
氧化铁 |
|
| 风化 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
| 无风化 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
| 氧化铜 |
氧化铅 |
氧化钡 |
五氧化二磷 |
氧化锶 |
氧化锡 |
二氧化硫 |
|
| 风化 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| 无风化 |
0 |
1 |
1 |
0 |
1 |
0 |
1 |
由上表易知，氧化钠、氧化钾、氧化铅、氧化钡、二氧化硫这五种化学元素对于玻璃的类型分类有影响。对于高钾玻璃的分类依据主要由化学成分为氧化钾的含量决定，对于铅钡玻璃的分类依据主要由化学成分为氧化钠、氧化铝、氧化钡、二氧化硫的含量决定。由于二氧化硅为玻璃的主要成分，所以对于二氧化硅不做结果判断。
对于第2小问，首先先根据类型，纹饰，表面风化可分为7个类别，7个类别再根据颜色的不同分为22个亚类，然后根据颜色找到相对应颜色的化学成分得到四个化学成分，分别为氧化铁(Fe2O3)，氧化铜(CuO)，氧化铅(PbO)，氧化锡(SnO2)。
对不同类型的玻璃进行类别分析及亚类划分的依据如下图所示：
| 氧化铅(PbO) |
0.0000 |
0.4229 |
0.2750 |
||
| 34.11% |
1.0000 |
1.4229 |
1.2750 |
||
| 1 |
34.11% |
33.77% |
33.89% |
||
图 3进行类别分析 图 4进行亚类划分
最后按颜色分为八类，应用单因素敏感度分析法[3]来进行敏感性分析见部分数据（余下见附录）
表 6对黑色氧化铅进行灵敏度分析
表 7对黑色氧化铜进行灵敏度分析
| 氧化铜(CuO) |
0.0000 |
0.0099 |
0.0059 |
|
| 34.11% |
1.0000 |
1.0099 |
1.0059 |
|
| 1 |
34.11% |
34.10% |
34.10% |
表 8对紫色氧化铅进行灵敏度分析
| 氧化铅(PbO) |
0.0000 |
0.0233 |
|
| 25.57% |
1.0000 |
1.0233 |
|
| 1 |
25.57% |
25.57% |
表 9对紫色氧化铜进行灵敏度分析
| 氧化铜(CuO) |
0.0000 |
0.3032 |
0.2314 |
|
| 25.57% |
1 |
1.3032 |
1.2314 |
|
| 1 |
25.57% |
25.57% |
25.57% |
由单元素敏感度分析法分析得知各个分类的敏感性分析前后变化不大说明模型是可靠的。
4.3 问题三
分析附件表3中未知类别玻璃文物的化学成分，鉴别其所属类型，对分类结果进行敏感性分析。
4.3.1 问题三的分析
为鉴别未知类别的玻璃文物所属类型，可利用第二问所得出的分类规律进行分析，首先，对未知类别文物所给化学成分数据进行累加求和，其次，进行归一化处理，最后，利用问题2的分类规律对附件表单3中的未知类别玻璃进行类别填充。通过查阅相关文献，利用单因素敏感度分析对数据进行灵敏度分析，选择氧化钾和氧化铅分别做单因素敏感性分析，利用Excel预测工作表相关功能进行敏感性分析。
4.3.2 问题三模型的建立和求解
对每种文物的化学成分数据进行累加求和，再对各化学成分进行归一化处理。由第二问所求的分类规律可知高钾玻璃的主要分类依据由化学成分氧化钾决定，铅钡玻璃的主要分类依据由化学成分氧化钠、氧化铅、氧化钡、二氧化硫决定且氧化铅占比最高。比较氧化钾和氧化铅的化学成分占比，当氧化钾的化学成分占比大于氧化铅的化学成分占比时所求的玻璃类型为高钾玻璃，反之则为铅钡玻璃。（当氧化钾的占比=氧化铅的占比时,比较二氧化硫，若二氧化硫存在时认为玻璃类型为高钾玻璃，反之则为铅钡玻璃）所填充部分数据如下表所示（完整表格见附录）：
表 10对未知类别玻璃鉴别其属性
| 文物编号 |
类型 |
二氧化硅 |
氧化钾 |
氧化铅 |
氧化钡 |
二氧化硫 |
| A1 |
高钾 |
0.789 |
0.005 |
|||
| A2 |
铅钡 |
0.392 |
0.356 |
|||
| A3 |
铅钡 |
0.323 |
0.014 |
0.400 |
0.047 |
|
| A4 |
铅钡 |
0.369 |
0.008 |
0.253 |
0.087 |
|
| A5 |
铅钡 |
0.645 |
0.004 |
0.123 |
0.022 |
|
| A6 |
高钾 |
0.940 |
0.014 |
|||
| A7 |
高钾 |
0.912 |
0.010 |
0.001 |
||
| A8 |
铅钡 |
0.511 |
0.002 |
0.212 |
0.113 |
0.023 |
由上表可知，文物编号为A1、A6、A7的文物玻璃类别为高钾玻璃，文物编号为A2、A3、A4、A5、A8的文物玻璃类别为铅钡玻璃。
将上表结果进行敏感性分析，利用单因素敏感度分析和Excel预测工作表进行敏感度分析[4]，结果如下表所示：
表 11对氧化铅和氧化钾进行灵敏度分析
| 氧化铅(PbO) |
0.0000 |
0.3563 |
0.3999 |
0.2529 |
0.1228 |
0.0000 |
0.0000 |
0.2124 |
||||||
| 16.16% |
1.0000 |
1.3563 |
1.3999 |
1.2529 |
1.1228 |
1.0000 |
1.0000 |
1.2124 |
||||||
| 1 |
16.16% |
22.15% |
25.27% |
22.71% |
19.03% |
16.16% |
16.16% |
19.73% |
||||||
| 氧化钾(K2O) |
0.0000 |
0.0000 |
0.0137 |
0.0082 |
0.0037 |
0.0136 |
0.0098 |
0.0023 |
||||||
| 16.16% |
1.0000 |
1.0000 |
1.0137 |
1.0082 |
1.0037 |
1.0136 |
1.0098 |
1.0023 |
||||||
| 1 |
16.16% |
16.16% |
16.39% |
16.30% |
16.22% |
16.39% |
16.33% |
16.20% |
||||||
敏感度随着氧化铅(PbO)，氧化钾(K2O)所占比例的提高而提高，氧化铅(PbO)，氧化钾(K2O)所占比例能够体现玻璃文物的敏感性。因为敏感性分析前后变化不大说明氧化铅(PbO)，氧化钾(K2O)比较稳健。
4.4 问题四
对于不同类别的玻璃样品，分析各化学成分之间的相互关联关系，并且对不同类别间化学成分的关联关系进行差异性性比较。
4.4.1 问题四的分析
分析不同类别玻璃样品的化学成分之间的关联关系，由问题二知，将玻璃文物样品分为7个类别，根据颜色得到4个化学成分，分别为氧化铁、氧化铜、氧化铅、氧化锡。对表单2中的化学成分依据所分的七个类别进行求期望值，将所求期望值根据类别及各自属性绘制出折线图，分析其关联性。对不同类别之间关于化学成分的关联关系比较其差异性，通过查阅相关文献，利用SPSS软件进行T检验可得出其关联关系的差异性。
4.4.2 问题四模型的建立和求解
通过查阅相关文献，得到关联关系是一种强依赖的关系，分为单项依赖和双向依赖。
为得出化学成分之间的关联关系，分别对七个类别和四种化学成分进行分析绘制出折线统计图如下图：
图 5关联关系折线图
由上图及关联关系的定义可知，七个不同类别下四种化学成分之间具有较强的依赖性。
对不同类别求其化学成分之间的差异性，运用SPSS软件进行T型检验，将 图 5导入到SPSS软件中进行差异性分析。结果如下表所示：
表 12对差异性进行T检验
| 单样本检验 |
||||||
| 检验值 = 0 |
||||||
| t |
自由度 |
Sig.（双尾） |
平均值差值 |
差值 95% 置信区间 |
||
| 下限 |
上限 |
|||||
| 氧化铁(Fe2O3) |
3.929 |
6 |
.008 |
1.08539% |
0.4094% |
1.7614% |
| 氧化铜(CuO) |
6.768 |
6 |
.001 |
1.88718% |
1.2049% |
2.5695% |
| 氧化铅(PbO) |
2.566 |
6 |
.043 |
19.43692% |
0.9013% |
37.9725% |
| 氧化锡(SnO2) |
1.359 |
6 |
.223 |
0.05740% |
-0.0459% |
0.1607% |
由表 12可知对化学成分的差异性进行T检验，得到氧化铁、氧化铜的差异性小，氧化铅、氧化锡的差异性大。
- 模型评价
5.1 模型优点
（1）统计规律可以保持各组内，统计资料的相同和组间资料的不同，有利于正确地认识事物的本质及其规律。
（2）统计规律是随机事件的整体性规律，它不是单个随机事件特点的简单叠加，而是事件系统所具有的必然性。
（3）单因素敏感性分析可以从多方案中快速找到最优方案。可以更好的寻求突破点加快分析进程。
（4）归一化方法操作方便，程序固定，操作要求不高。
5.2 模型缺点
（1）统计规律除非在一个稳定的群体中，连续进行同样的现况调查，否则难以调查，过程长短不确定。
（2）单因素敏感性分析在一定程度上带有自我性、臆测性，它是不全面的，容易造成低估评价风险后果，具有较大的误差。
5.3 模型改进
用随机抽样的方法抽取可加快进程缩短时间，应用多因素敏感性分析让敏感性分析更全面。
- 参考文献
[1] baike.baidu.com/item/归一化方法
[2] zhuanlan.zhihu.com/p/127962782统计规律
[3]卢佳欣.基于单因素敏感性分析的汽车三滤纸项目[J].黑龙江造纸,2018,46(04):10-14.
[4]郁玉环.利用Excel自动实现投资项目敏感性分析[J].会计之友,2014(06):117-120.
附 录
| 支撑材料文件列表 |
||||
| 序号 |
名称 |
说明 |
类型 |
备注 |
| 1 |
表单二归一化处理后的数据 |
对附录表单二数据归一化处理 |
xlsx文件 |
|
| 2 |
matlab代码 |
本文涉及的matlab代码文本 |
txt文件 |
|
| 3 |
预测值 |
问题二第二小问的预测的其风化前的化学成分含量 |
xlsx文件 |
|
| 4 |
亚类划分 |
问题二亚类划分及其划分结果 |
xlsx文件 |
|
| 5 |
所属类型 |
问题三对附件表单3中文物所属类型 |
xlsx文件 |
|
| 6 |
敏感度分析1 |
问题二敏感度分析 |
xlsx文件 |
|
| 7 |
敏感度分析2 |
问题三敏感度分析 |
xlsx文件 |
|
问题1第2问
| 文物采样点 |
类型 |
表面风化 |
二氧化硅(SiO2) |
氧化钠(Na2O) |
氧化钾(K2O) |
|||||
| 01 |
高钾 |
无风化 |
0.685821362 |
0 |
0.10066625 |
|||||
| 02 |
铅钡 |
风化 |
0.199401131 |
0 |
0 |
|||||
| 03部位1 |
高钾 |
无风化 |
0.638068594 |
0 |
0.113459745 |
|||||
| 03部位2 |
高钾 |
无风化 |
0.817069409 |
0 |
0.096863753 |
|||||
| 04 |
高钾 |
无风化 |
0.710275587 |
0 |
0.102346071 |
|||||
| 05 |
高钾 |
无风化 |
0.60128388 |
0.029142042 |
0.12767475 |
|||||
| 06部位1 |
高钾 |
无风化 |
0.662331064 |
0.021339295 |
0.147545981 |
|||||
| 06部位2 |
高钾 |
无风化 |
0.778319123 |
0 |
0 |
|||||
| 07 |
高钾 |
风化 |
0.938366562 |
0 |
0 |
|||||
| 08 |
铅钡 |
风化 |
0.232824427 |
0 |
0 |
|||||
| 08严重风化点 |
铅钡 |
风化 |
0.316023417 |
0 |
0 |
|||||
| 09 |
高钾 |
风化 |
0.94697198 |
0 |
0.010143618 |
|||||
| 10 |
高钾 |
风化 |
0.929087262 |
0 |
0 |
|||||
| 11 |
铅钡 |
风化 |
0.274899968 |
0 |
0 |
|||||
| 12 |
高钾 |
风化 |
0.952390498 |
0 |
0.005913601 |
|||||
| 13 |
高钾 |
无风化 |
0.605119385 |
0 |
0.077701335 |
|||||
| 14 |
高钾 |
无风化 |
0.624089806 |
0 |
0.125101133 |
|||||
| 16 |
高钾 |
无风化 |
0.683885968 |
0 |
0.07450465 |
|||||
| 18 |
高钾 |
无风化 |
0.631010101 |
0.034141414 |
0.124040404 |
|||||
| 19 |
铅钡 |
风化 |
0.196990716 |
0 |
0.004695337 |
|||||
| 20 |
铅钡 |
无风化 |
0.422576632 |
0 |
0.008030766 |
|||||
| 21 |
高钾 |
无风化 |
0.8705 |
0 |
0.0519 |
|||||
| 22 |
高钾 |
风化 |
0.96954213 |
0 |
0.009217513 |
|||||
| 23未风化点 |
铅钡 |
无风化 |
0.685063923 |
0 |
0 |
|||||
| 24 |
铅钡 |
无风化 |
0.508507989 |
0.028117867 |
0 |
|||||
| 25未风化点 |
铅钡 |
无风化 |
0.557409326 |
0.082072539 |
0 |
|||||
| 26 |
铅钡 |
风化 |
0.273596939 |
0.012967687 |
0 |
|||||
| 26严重风化点 |
铅钡 |
风化 |
0.131073088 |
0 |
0 |
|||||
| 27 |
高钾 |
风化 |
0.9235 |
0 |
0.0074 |
|||||
| 28未风化点 |
铅钡 |
无风化 |
0.464410976 |
0 |
0 |
|||||
| 29未风化点 |
铅钡 |
无风化 |
0.521430043 |
0.023799712 |
0 |
|||||
| 30部位1 |
铅钡 |
无风化 |
0.529919803 |
0.047912811 |
0.002981699 |
|||||
| 30部位2 |
铅钡 |
无风化 |
0.524310521 |
0.058018386 |
0.003575077 |
|||||
| 31 |
铅钡 |
无风化 |
0.350587034 |
0 |
0.0143951 |
|||||
| 32 |
铅钡 |
无风化 |
0.523007856 |
0.058565453 |
0.001530456 |
|||||
| 33 |
铅钡 |
无风化 |
0.55588355 |
0 |
0.003053746 |
|||||
| 34 |
铅钡 |
风化 |
0.25815588 |
0 |
0 |
|||||
| 35 |
铅钡 |
无风化 |
0.647938931 |
0.030941476 |
0.001119593 |
|||||
| 36 |
铅钡 |
风化 |
0.352133347 |
0 |
0.002201489 |
|||||
| 37 |
铅钡 |
无风化 |
0.623144194 |
0.027049014 |
0.001118568 |
|||||
| 38 |
铅钡 |
风化 |
0.301465969 |
0 |
0 |
|||||
| 39 |
铅钡 |
风化 |
0.224475018 |
0 |
0 |
|||||
| 40 |
铅钡 |
风化 |
0.17653735 |
0 |
0 |
|||||
| 41 |
铅钡 |
风化 |
0.366899098 |
0 |
0.002563577 |
|||||
| 42未风化点1 |
铅钡 |
无风化 |
0.669612923 |
0 |
0 |
|||||
| 42未风化点2 |
铅钡 |
无风化 |
0.559768833 |
0 |
0.002534726 |
|||||
| 43部位1 |
铅钡 |
风化 |
0.405305746 |
0.022738912 |
0.001433985 |
|||||
| 43部位2 |
铅钡 |
风化 |
0.046925896 |
0 |
0 |
|||||
| 44未风化点 |
铅钡 |
无风化 |
0.706568011 |
0 |
0.002128522 |
|||||
| 45 |
铅钡 |
无风化 |
0.689836863 |
0 |
0.002634512 |
|||||
| 46 |
铅钡 |
无风化 |
0.374164134 |
0 |
0 |
|||||
| 47 |
铅钡 |
无风化 |
0.323017799 |
0 |
0 |
|||||
| 48 |
铅钡 |
风化 |
0.169524196 |
0 |
0 |
|||||
| 49 |
铅钡 |
风化 |
0.334077305 |
0.014000203 |
0 |
|||||
| 49未风化点 |
铅钡 |
无风化 |
0.612792575 |
0.030871671 |
0.002017756 |
|||||
| 50 |
铅钡 |
风化 |
0.300121507 |
0 |
0 |
|||||
| 50未风化点 |
铅钡 |
无风化 |
0.633760513 |
0.009211053 |
0.003003604 |
|||||
| 51部位1 |
铅钡 |
风化 |
0.265795869 |
0 |
0 |
|||||
| 51部位2 |
铅钡 |
风化 |
0.307715674 |
0 |
0.003442689 |
|||||
| 52 |
铅钡 |
风化 |
0.537763437 |
0.008066956 |
0.003226782 |
|||||
| 53未风化点 |
铅钡 |
无风化 |
0.755402161 |
0 |
0.0015006 |
|||||
| 54 |
铅钡 |
风化 |
0.223537674 |
0 |
0.003210595 |
|||||
| 54严重风化点 |
铅钡 |
风化 |
0.198256862 |
0 |
0 |
|||||
| 55 |
铅钡 |
无风化 |
0.601320264 |
0 |
0.00230046 |
|||||
| 56 |
铅钡 |
风化 |
0.201763174 |
0 |
0 |
|||||
| 57 |
铅钡 |
风化 |
0.363199519 |
0 |
0.010511563 |
|||||
| 58 |
铅钡 |
风化 |
0.037240965 |
0 |
0.004004405 |
|||||
| 氧化钙(CaO) |
氧化镁(MgO) |
氧化铝(Al2O3) |
氧化铁(Fe2O3) |
氧化铜(CuO) |
氧化铅(PbO) |
|||||
| 0.074120341 |
0.01623985 |
0.067041432 |
0.02144493 |
0.022694149 |
0 |
|||||
| 0.03537762 |
0.005212377 |
0.020738605 |
0.003659754 |
0.012531884 |
0.487967173 |
|||||
| 0.076157911 |
0.018340068 |
0.077712154 |
0.027147446 |
0.033882499 |
0 |
|||||
| 0 |
0.015732648 |
0.031362468 |
0 |
0 |
0 |
|||||
| 0.064747464 |
0.008913021 |
0.040262268 |
0.017826042 |
0.039647577 |
0 |
|||||
| 0.088648869 |
0 |
0.062767475 |
0.029345832 |
0.048196454 |
0 |
|||||
| 0.084036175 |
0.005284016 |
0.062798496 |
0.004267859 |
0.010872879 |
0.001117773 |
|||||
| 0.047807552 |
0.012383272 |
0.062829882 |
0.024056029 |
0.033292732 |
0.010150223 |
|||||
| 0.009513207 |
0.005465034 |
0.025402287 |
0.002024087 |
0.015585467 |
0 |
|||||
| 0.055943293 |
0.015812432 |
0.027371865 |
0.004580153 |
0.008178844 |
0.559869138 |
|||||
| 0.013117953 |
0 |
0.020056375 |
0 |
0.008564614 |
0.447202949 |
|||||
| 0.007231094 |
0 |
0.014663051 |
0.002912524 |
0.016571256 |
0 |
|||||
| 0.010732197 |
0 |
0.019859579 |
0.001705115 |
0.032497492 |
0 |
|||||
| 0.014166757 |
0 |
0.023575214 |
0 |
0.012544609 |
0.487725749 |
|||||
| 0.006214293 |
0 |
0.01323043 |
0.003207377 |
0.015535732 |
0 |
|||||
| 0.054734925 |
0.017503035 |
0.101679482 |
0.061108863 |
0.022055848 |
0.003541076 |
|||||
| 0.059364887 |
0.011225728 |
0.055622977 |
0.02184466 |
0.051476537 |
0.014259709 |
|||||
| 0 |
0.020016175 |
0.112717347 |
0.024160938 |
0.02537404 |
0.002021836 |
|||||
| 0.083131313 |
0.006666667 |
0.093232323 |
0.005050505 |
0.004747475 |
0.016363636 |
|||||
| 0.05292925 |
0.02913243 |
0.035535162 |
0.019101483 |
0.002027532 |
0.470814214 |
|||||
| 0 |
0 |
0.06164461 |
0.017079516 |
0.054066282 |
0.10519172 |
|||||
| 0.0201 |
0 |
0.0406 |
0 |
0.0078 |
0.0025 |
|||||
| 0.002103998 |
0 |
0.008115419 |
0.002604949 |
0.00841599 |
0 |
|||||
| 0.003949693 |
0 |
0.014967259 |
0.001766968 |
0.001663029 |
0.229186155 |
|||||
| 0.011724424 |
0 |
0.015044615 |
0 |
0.008923013 |
0.34156464 |
|||||
| 0.005181347 |
0.007357513 |
0.014715026 |
0 |
0.030984456 |
0.175958549 |
|||||
| 0.024128401 |
0.005846088 |
0.012329932 |
0.002444728 |
0.007440476 |
0.504039116 |
|||||
| 0.055344318 |
0.009400084 |
0.023764259 |
0.008027038 |
0.056506126 |
0.632129278 |
|||||
| 0.0166 |
0.0064 |
0.035 |
0.0035 |
0.0055 |
0 |
|||||
| 0.032184857 |
0.005570456 |
0.042913142 |
0 |
0.007220961 |
0.315762327 |
|||||
| 0.00649083 |
0 |
0.01957552 |
0.015969503 |
0.011539254 |
0.328662683 |
|||||
| 0.008945096 |
0.006271849 |
0.03146206 |
0 |
0.006683117 |
0.261155665 |
|||||
| 0 |
0.011848825 |
0.057814096 |
0 |
0.027783453 |
0.205515832 |
|||||
| 0.045839714 |
0.010005105 |
0.044410413 |
0.021643696 |
0 |
0.400408372 |
|||||
| 0.008060402 |
0.011121314 |
0.036016733 |
0 |
0.027242118 |
0.223242526 |
|||||
| 0.021172638 |
0.012214984 |
0.066164495 |
0.012927524 |
0.004580619 |
0.234324104 |
|||||
| 0.037553761 |
0.012482954 |
0.055071856 |
0.012482954 |
0.014371132 |
0.422112661 |
|||||
| 0.007938931 |
0.011603053 |
0.061679389 |
0 |
0.005496183 |
0.139033079 |
|||||
| 0.03679631 |
0.007443128 |
0.028200021 |
0 |
0.051682566 |
0.266170458 |
|||||
| 0.008541794 |
0.007524914 |
0.050844011 |
0 |
0.005389465 |
0.162599146 |
|||||
| 0.047958115 |
0.01539267 |
0.056335079 |
0.028691099 |
0.007329843 |
0.357905759 |
|||||
| 0.066204614 |
0.009827247 |
0.035274646 |
0.014378815 |
0.015620151 |
0.462915072 |
|||||
| 0 |
0.011452745 |
0.037659926 |
0 |
0.013825836 |
0.603177879 |
|||||
| 0.007998359 |
0 |
0.016611977 |
0.004819524 |
0.015484003 |
0.477337982 |
|||||
| 0.016255207 |
0.009041959 |
0.031596058 |
0.046632124 |
0.004470182 |
0.168139795 |
|||||
| 0 |
0.016931968 |
0.048565345 |
0 |
0.007806955 |
0.2560073 |
|||||
| 0.003789819 |
0 |
0.016388405 |
0.003277681 |
0.006965072 |
0.426200963 |
|||||
| 0.032471498 |
0 |
0.01129886 |
0 |
0.031962541 |
0.330313518 |
|||||
| 0.004662477 |
0 |
0.023920535 |
0.01013582 |
0.00111494 |
0.200283803 |
|||||
| 0.01357787 |
0.010132739 |
0.047623873 |
0.004154423 |
0.003343804 |
0.173675144 |
|||||
| 0.04295846 |
0.005167173 |
0.039108409 |
0.027760892 |
0 |
0.382370821 |
|||||
| 0.004753236 |
0 |
0.016080097 |
0 |
0.085558252 |
0.294700647 |
|||||
| 0.018971289 |
0 |
0.004565284 |
0.001927564 |
0 |
0.712285685 |
|||||
| 0.006898651 |
0 |
0.026072842 |
0.002942072 |
0.007405904 |
0.500253627 |
|||||
| 0.021589992 |
0 |
0.128026634 |
0.007768362 |
0.004338176 |
0.137308313 |
|||||
| 0.029667882 |
0.005974079 |
0.036148238 |
0.013466991 |
0.035540705 |
0.433576347 |
|||||
| 0.029835803 |
0.014917901 |
0.143572287 |
0.008109732 |
0.007408891 |
0.123247897 |
|||||
| 0.011239368 |
0 |
0.005062778 |
0 |
0.00891049 |
0.617962738 |
|||||
| 0.035338194 |
0.00799919 |
0.03564196 |
0.008707979 |
0.031692993 |
0.398440664 |
|||||
| 0.028436019 |
0.01552889 |
0.137642432 |
0.010386206 |
0 |
0.158414843 |
|||||
| 0.006402561 |
0.010004002 |
0.023509404 |
0 |
0.004701881 |
0.161664666 |
|||||
| 0.032005619 |
0.01284238 |
0.041637403 |
0 |
0.008327481 |
0.55643624 |
|||||
| 0.014425967 |
0 |
0.007012623 |
0 |
0.105890603 |
0.295832498 |
|||||
| 0.00890178 |
0 |
0.027205441 |
0 |
0.030106021 |
0.172434487 |
|||||
| 0.014826688 |
0 |
0.013424163 |
0 |
0.104287718 |
0.287317171 |
|||||
| 0.023425768 |
0.011812994 |
0.057363099 |
0.018620483 |
0.002602863 |
0.474822305 |
|||||
| 0.030133146 |
0 |
0.011812994 |
0 |
0.036039644 |
0.299529482 |
|||||
| 氧化钡(BaO) |
五氧化二磷(P2O5) |
氧化锶(SrO) |
氧化锡(SnO2) |
二氧化硫(SO2) |
||||||
| 0 |
0.008224027 |
0 |
0 |
0.003747658 |
||||||
| 0.157480315 |
0.070311634 |
0.007319508 |
0 |
0 |
||||||
| 0 |
0.009739923 |
0.000621697 |
0 |
0.004869962 |
||||||
| 0 |
0.013984576 |
0.000719794 |
0.024267352 |
0 |
||||||
| 0 |
0.011986477 |
0 |
0 |
0.003995492 |
||||||
| 0 |
0.012940697 |
0 |
0 |
0 |
||||||
| 0 |
0 |
0.000406463 |
0 |
0 |
||||||
| 0.01999594 |
0.011165246 |
0 |
0 |
0 |
||||||
| 0 |
0.003643356 |
0 |
0 |
0 |
||||||
| 0 |
0.095419847 |
0 |
0 |
0 |
||||||
| 0.167497832 |
0.02753686 |
0 |
0 |
0 |
||||||
| 0 |
0.001506478 |
0 |
0 |
0 |
||||||
| 0 |
0.006118355 |
0 |
0 |
0 |
||||||
| 0.187087704 |
0 |
0 |
0 |
0 |
||||||
| 0 |
0.003508069 |
0 |
0 |
0 |
||||||
| 0.009813841 |
0.045528126 |
0.001214083 |
0 |
0 |
||||||
| 0.028923948 |
0.007079288 |
0.001011327 |
0 |
0 |
||||||
| 0.013950667 |
0.042256369 |
0.00111201 |
0 |
0 |
||||||
| 0 |
0.001616162 |
0 |
0 |
0 |
||||||
| 0.104151104 |
0.079607299 |
0.005015473 |
0 |
0 |
||||||
| 0.266372582 |
0.065037892 |
0 |
0 |
0 |
||||||
| 0 |
0.0066 |
0 |
0 |
0 |
||||||
| 0 |
0 |
0 |
0 |
0 |
||||||
| 0.059037522 |
0.004365451 |
0 |
0 |
0 |
||||||
| 0.082485993 |
0.003631459 |
0 |
0 |
0 |
||||||
| 0.122901554 |
0 |
0.003419689 |
0 |
0 |
||||||
| 0.091836735 |
0.060693027 |
0.004676871 |
0 |
0 |
||||||
| 0.076996198 |
0 |
0.006759611 |
0 |
0 |
||||||
| 0 |
0.0021 |
0 |
0 |
0 |
||||||
| 0.0641634 |
0.065401279 |
0.002372602 |
0 |
0 |
||||||
| 0.068514321 |
0.001957552 |
0.002060581 |
0 |
0 |
||||||
| 0.094900267 |
0.001028172 |
0.008739461 |
0 |
0 |
||||||
| 0.11113381 |
0 |
0 |
0 |
0 |
||||||
| 0.105053599 |
0 |
0.003573252 |
0.004083716 |
0 |
||||||
| 0.106825834 |
0.000816243 |
0.003571064 |
0 |
0 |
||||||
| 0.042650651 |
0.043973941 |
0.003053746 |
0 |
0 |
||||||
| 0.093779503 |
0.084968006 |
0.004091052 |
0.004930242 |
0 |
||||||
| 0.091501272 |
0 |
0.002748092 |
0 |
0 |
||||||
| 0.153160709 |
0.098333159 |
0.003878813 |
0 |
0 |
||||||
| 0.111450071 |
0 |
0.002338824 |
0 |
0 |
||||||
| 0.063874346 |
0.116230366 |
0.004816754 |
0 |
0 |
||||||
| 0.033722975 |
0.132719561 |
0.004861901 |
0 |
0 |
||||||
| 0 |
0.145790343 |
0.011555922 |
0 |
0 |
||||||
| 0.102543068 |
0.003486464 |
0.002255947 |
0 |
0 |
||||||
| 0.034745504 |
0.016458397 |
0.003047851 |
0 |
0 |
||||||
| 0.101997364 |
0.002027781 |
0.004359728 |
0 |
0 |
||||||
| 0.110929018 |
0.000716993 |
0.002253406 |
0 |
0 |
||||||
| 0.311685668 |
0.076954397 |
0.005394951 |
0 |
0.152992671 |
||||||
| 0.049462802 |
0.001723089 |
0 |
0 |
0 |
||||||
| 0.040936265 |
0.010538048 |
0.001215929 |
0.00233053 |
0 |
||||||
| 0.104863222 |
0.014285714 |
0.004863222 |
0.004457953 |
0 |
||||||
| 0.265271036 |
0.001415858 |
0.009203074 |
0 |
0 |
||||||
| 0.067870549 |
0.017956782 |
0.006898651 |
0 |
0 |
||||||
| 0.09932028 |
0.004869636 |
0.004159481 |
0 |
0 |
||||||
| 0.052663438 |
0 |
0.002623083 |
0 |
0 |
||||||
| 0.054171729 |
0.089408667 |
0.001923856 |
0 |
0 |
||||||
| 0.020324389 |
0.004104926 |
0.002503004 |
0 |
0 |
||||||
| 0.073106521 |
0.011745646 |
0.00617659 |
0 |
0 |
||||||
| 0.077561766 |
0.091028757 |
0.002430134 |
0 |
0 |
||||||
| 0.073711808 |
0.011092064 |
0.002520924 |
0.01320964 |
0 |
||||||
| 0.035514206 |
0.00130052 |
0 |
0 |
0 |
||||||
| 0.070633089 |
0.042540383 |
0.008829136 |
0 |
0 |
||||||
| 0.323081547 |
0.031356442 |
0.004508115 |
0 |
0.019635344 |
||||||
| 0.103420684 |
0.014602921 |
0.00310062 |
0 |
0.036607321 |
||||||
| 0.312863154 |
0.035964737 |
0.003706672 |
0 |
0.025846524 |
||||||
| 0 |
0.035739313 |
0.001902092 |
0 |
0 |
||||||
| 0.354890379 |
0.060466513 |
0.006206828 |
0 |
0.159675643 |
||||||
第1题第3小问预测值
| 文物采样点 |
类型 |
二氧化硅(SiO2) |
氧化钠(Na2O) |
氧化钾(K2O) |
氧化钙(CaO) |
氧化镁(MgO) |
氧化铝(Al2O3) |
氧化铁(Fe2O3) |
||||
| 02 |
铅钡 |
65.13 |
1.02 |
1.19 |
1.06 |
7.23 |
2.45 |
|||||
| 07 |
高钾 |
62.42 |
6.19 |
6.23 |
2.07 |
|||||||
| 08 |
铅钡 |
48.99 |
0.33 |
2.84 |
||||||||
| 08严重风化点 |
铅钡 |
33.46 |
2.04 |
2.61 |
||||||||
| 09 |
高钾 |
64.81 |
9.29 |
5.74 |
5.57 |
2.22 |
||||||
| 10 |
高钾 |
66.56 |
9.62 |
5.33 |
5.06 |
2.16 |
||||||
| 11 |
铅钡 |
62.44 |
0.18 |
2.36 |
0.59 |
4.19 |
||||||
| 12 |
高钾 |
64.08 |
9.71 |
5.84 |
5.71 |
2.19 |
||||||
| 19 |
铅钡 |
58.49 |
1.78 |
0.47 |
5.07 |
1.92 |
||||||
| 22 |
高钾 |
62.14 |
9.44 |
6.78 |
1.26 |
7.75 |
2.25 |
|||||
| 26 |
铅钡 |
48.64 |
0.29 |
2.2 |
||||||||
| 26严重风化点 |
铅钡 |
32.57 |
0.37 |
1.86 |
2.68 |
|||||||
| 27 |
高钾 |
62.51 |
6.06 |
1.16 |
6.76 |
2.1 |
||||||
| 34 |
铅钡 |
64.63 |
0.22 |
3.12 |
1.06 |
|||||||
| 36 |
铅钡 |
68.42 |
4.61 |
0.11 |
3.1 |
0.91 |
||||||
| 38 |
铅钡 |
61.78 |
3.77 |
4.07 |
0.88 |
|||||||
| 39 |
铅钡 |
55.1 |
2 |
|||||||||
| 40 |
铅钡 |
45.56 |
0.72 |
1.95 |
0.78 |
|||||||
| 41 |
铅钡 |
47.31 |
0.41 |
3.81 |
2.61 |
4.83 |
2.38 |
|||||
| 43部位1 |
铅钡 |
41.26 |
4.09 |
0.77 |
3.75 |
1.35 |
||||||
| 43部位2 |
铅钡 |
50.55 |
5.25 |
0.83 |
4.91 |
1.98 |
||||||
| 48 |
铅钡 |
82.18 |
3.19 |
0.29 |
1.67 |
1.42 |
15.15 |
1.62 |
||||
| 49 |
铅钡 |
57.64 |
3.43 |
1.35 |
6.88 |
3.33 |
||||||
| 50 |
铅钡 |
46.83 |
2.04 |
0.35 |
3.37 |
0.92 |
||||||
| 51部位1 |
铅钡 |
53.46 |
2.43 |
1.07 |
6.75 |
1.78 |
||||||
| 51部位2 |
铅钡 |
50.2 |
3.98 |
1.33 |
4.01 |
1.01 |
||||||
| 52 |
铅钡 |
54.59 |
3.61 |
1.12 |
0.43 |
2.66 |
0.82 |
|||||
| 54 |
铅钡 |
51.13 |
0.29 |
2.04 |
1.16 |
5.65 |
||||||
| 54严重风化点 |
铅钡 |
45.96 |
0.99 |
5.15 |
||||||||
| 56 |
铅钡 |
58 |
0.06 |
3.35 |
||||||||
| 57 |
铅钡 |
54.27 |
0.16 |
3.68 |
||||||||
| 58 |
铅钡 |
59.24 |
0.31 |
2.34 |
0.67 |
5.02 |
1.45 |
|||||
| 文物采样点 |
类型 |
氧化铜(CuO) |
氧化铅(PbO) |
氧化钡(BaO) |
五氧化二磷(P2O5) |
氧化锶(SrO) |
氧化锡(SnO2) |
二氧化硫(SO2) |
||||
| 02 |
铅钡 |
28.64 |
0.1 |
|||||||||
| 07 |
高钾 |
4.18 |
1.7 |
|||||||||
| 08 |
铅钡 |
9.68 |
9.89 |
27.67 |
0.28 |
|||||||
| 08严重风化点 |
铅钡 |
2.41 |
13.66 |
27.06 |
3.69 |
0.44 |
10.5 |
|||||
| 09 |
高钾 |
2.49 |
1.44 |
|||||||||
| 10 |
高钾 |
1.78 |
||||||||||
| 11 |
铅钡 |
4.2 |
6.6 |
11.05 |
5.51 |
0.28 |
||||||
| 12 |
高钾 |
2.59 |
1.24 |
|||||||||
| 19 |
铅钡 |
2.78 |
24.03 |
1.79 |
4.96 |
0.1 |
||||||
| 22 |
高钾 |
1.49 |
1.3 |
|||||||||
| 26 |
铅钡 |
9.84 |
10.74 |
28.69 |
0.36 |
|||||||
| 26严重风化点 |
铅钡 |
2.87 |
11.13 |
31.89 |
2.17 |
0.53 |
11.42 |
|||||
| 27 |
高钾 |
2.48 |
1.45 |
|||||||||
| 34 |
铅钡 |
0.78 |
27.76 |
6.44 |
0.13 |
|||||||
| 36 |
铅钡 |
22.82 |
7.27 |
0.13 |
||||||||
| 38 |
铅钡 |
0 |
30.52 |
6.23 |
0.32 |
|||||||
| 39 |
铅钡 |
0.15 |
42.24 |
3.66 |
0.52 |
|||||||
| 40 |
铅钡 |
51.42 |
3.13 |
0.59 |
||||||||
| 41 |
铅钡 |
25.33 |
6.2 |
3.59 |
0.38 |
|||||||
| 43部位1 |
铅钡 |
4.62 |
41.06 |
3.73 |
0.55 |
|||||||
| 43部位2 |
铅钡 |
0.78 |
25.96 |
8.96 |
0.38 |
|||||||
| 48 |
铅钡 |
3.75 |
0.16 |
0.84 |
||||||||
| 49 |
铅钡 |
15.39 |
2.54 |
7.23 |
0.37 |
|||||||
| 50 |
铅钡 |
0.4 |
25.21 |
10.64 |
2.47 |
0.57 |
||||||
| 51部位1 |
铅钡 |
0.64 |
21.45 |
5.38 |
4.23 |
0.3 |
||||||
| 51部位2 |
铅钡 |
0.02 |
32.55 |
4.88 |
||||||||
| 52 |
铅钡 |
28.63 |
5.08 |
1.84 |
0.35 |
|||||||
| 54 |
铅钡 |
0.1 |
36.67 |
3.48 |
0.37 |
0.79 |
||||||
| 54严重风化点 |
铅钡 |
0.61 |
39.67 |
10.26 |
1.03 |
|||||||
| 56 |
铅钡 |
0.06 |
22.46 |
11.89 |
||||||||
| 57 |
铅钡 |
0.43 |
26.31 |
13.74 |
||||||||
| 58 |
铅钡 |
2.4 |
20.56 |
4.1 |
0.15 |
|||||||
第一问第3小问的期望值差值
问题2第2小问
蓝绿色敏感性分析
| 类型 |
二氧化硅(SiO2) |
氧化钠(Na2O) |
氧化钾(K2O) |
氧化钙(CaO) |
氧化镁(MgO) |
氧化铝(Al2O3) |
氧化铁(Fe2O3) |
| 高钾 |
-25.10 |
0.71 |
8.97 |
4.57 |
0.90 |
4.80 |
1.70 |
| 铅钡 |
30.08 |
1.50 |
0.09 |
-1.46 |
-0.03 |
1.49 |
0.15 |
| 类型 |
氧化铜(CuO) |
氧化铅(PbO) |
氧化钡(BaO) |
五氧化二磷(P2O5) |
氧化锶(SrO) |
氧化锡(SnO2) |
二氧化硫(SO2) |
| 高钾 |
0.93 |
0.42 |
0.61 |
1.14 |
0.04 |
0.20 |
0.11 |
| 铅钡 |
-0.85 |
-22.31 |
-2.87 |
-4.38 |
-0.16 |
-0.02 |
-1.22 |
| 氧化铁(Fe2O3) |
0.0000 |
0.0000 |
0.0257 |
0.0027 |
0.0178 |
|
| 12.04% |
1.0000 |
1.0000 |
1.0257 |
1.0027 |
1.0178 |
|
| 1 |
12.04% |
12.04% |
12.01% |
12.04% |
12.02% |
浅绿色敏感性分析
| 氧化铅(PbO) |
0.1760 |
0.4675 |
0.0046 |
0.0000 |
0.0000 |
|
| 12.04% |
1.1760 |
1.4675 |
1.0046 |
1.0000 |
1.0000 |
|
| 1 |
11.88% |
11.61% |
12.03% |
12.04% |
12.04% |
| 氧化铁(Fe2O3) |
0.0000 |
0.0191 |
0.0060 |
|
| 33.02% |
1.0000 |
1.0191 |
1.0060 |
|
| 1 |
33.02% |
33.02% |
33.02% |
绿色敏感性分析
| 氧化铅(PbO) |
0.0000 |
0.4708 |
0.2147 |
|
| 33.02% |
1.0000 |
1.4708 |
1.2147 |
|
| 1 |
0.330248158 |
0.330248158 |
0.330248158 |
| 氧化铁(Fe2O3) |
0.0000 |
|
| 17.08% |
1.0000 |
|
| 1 |
17.08% |
| 氧化铅(PbO) |
0 |
0.3416 |
|
| 17.08% |
1.0000 |
1.3416 |
|
| 1 |
0.17078232 |
0.17078232 |
浅蓝敏感性分析
| 氧化铁(Fe2O3) |
0.0186 |
0.0037 |
0.0052 |
0.0160 |
0.0168 |
|
| 28.47% |
1.0186 |
1.0037 |
1.0052 |
1.0160 |
1.0168 |
|
| 1 |
28.47% |
28.47% |
28.47% |
28.47% |
28.47% |
| 氧化铅(PbO) |
0.4748 |
0.1787 |
0.5009 |
0.3287 |
0.0006 |
|
| 28.47% |
1.4748 |
1.1787 |
1.5009 |
1.3287 |
1.0006 |
|
| 1 |
28.47% |
28.47% |
28.47% |
28.47% |
28.47% |
深绿敏感性分析
| 氧化铁(Fe2O3) |
0.0028 |
0.0000 |
0.0051 |
|
| 22.70% |
1.0028 |
1.0000 |
1.0051 |
|
| 1 |
22.70% |
22.70% |
22.70% |
|
| 氧化铅(PbO) |
0.5054 |
0.1670 |
0.0164 |
|
| 22.70% |
1.5054 |
1.1670 |
1.0164 |
|
| 1.00% |
22.70% |
22.70% |
22.70% |
深蓝敏感性分析
| 氧化铁(Fe2O3) |
0.0247 |
0.0000 |
|
| 18.33% |
1.0247 |
1.0000 |
|
| 1 |
18.33% |
18.33% |
| 氧化铅(PbO) |
0.3914 |
0.0000 |
|
| 0.1833 |
1.3914 |
1.0000 |
|
| 1 |
18.33% |
18.33% |
第3问第1小问
| 文物编号 |
表面风化 |
类型 |
二氧化硅(SiO2) |
氧化钠(Na2O) |
氧化钾(K2O) |
氧化钙(CaO) |
氧化镁(MgO) |
| A1 |
无风化 |
铅钡 |
0.788600724 |
0.061117813 |
0.018697226 |
||
| A2 |
风化 |
铅钡 |
0.392085584 |
0.079248027 |
|||
| A3 |
无风化 |
铅钡 |
0.322792483 |
0.01374015 |
0.072640938 |
0.008183471 |
|
| A4 |
无风化 |
铅钡 |
0.369479167 |
0.008229167 |
0.030104167 |
0.0109375 |
|
| A5 |
风化 |
铅钡 |
0.645352339 |
0.012045774 |
0.003714114 |
0.016462558 |
0.023489259 |
| A6 |
风化 |
高钾 |
0.940161453 |
0.013622603 |
0.006458123 |
0.002119072 |
|
| A7 |
风化 |
高钾 |
0.911581694 |
0.009835407 |
0.011240466 |
||
| A8 |
无风化 |
铅钡 |
0.51130226 |
0.00230046 |
0.00890178 |
||
| 文物编号 |
表面风化 |
类型 |
氧化铝(Al2O3) |
氧化铁(Fe2O3) |
氧化铜(CuO) |
氧化铅(PbO) |
氧化钡(BaO) |
| A1 |
无风化 |
铅钡 |
0.072677925 |
0.021612384 |
0.021210294 |
||
| A2 |
风化 |
铅钡 |
0.024200249 |
0.356252597 |
|||
| A3 |
无风化 |
铅钡 |
0.02960194 |
0.071327541 |
0.002121641 |
0.399878763 |
0.04738331 |
| A4 |
无风化 |
铅钡 |
0.073645833 |
0.0671875 |
0.01 |
0.252916667 |
0.0865625 |
| A5 |
风化 |
铅钡 |
0.127986348 |
0.008130897 |
0.009435856 |
0.122766513 |
0.021682393 |
| A6 |
风化 |
高钾 |
0.015338042 |
0.002724521 |
0.017457114 |
||
| A7 |
风化 |
高钾 |
0.050782818 |
0.002408671 |
0.011742272 |
||
| A8 |
无风化 |
铅钡 |
0.021204241 |
0.090118024 |
0.212442488 |
0.113422685 |
|
| 文物编号 |
表面风化 |
类型 |
五氧化二磷(P2O5) |
氧化锶(SrO) |
氧化锡(SnO2) |
二氧化硫(SO2) |
|
| A1 |
无风化 |
铅钡 |
0.010655408 |
0.000301568 |
0.005126659 |
||
| A2 |
风化 |
铅钡 |
0.148213544 |
||||
| A3 |
无风化 |
铅钡 |
0.027076177 |
0.005253587 |
|||
| A4 |
无风化 |
铅钡 |
0.088020833 |
0.002916667 |
|||
| A5 |
风化 |
铅钡 |
0.001907248 |
0.00210801 |
0.004918691 |
||
| A6 |
风化 |
高钾 |
0.002119072 |
||||
| A7 |
风化 |
高钾 |
0.001304697 |
0.001103974 |
|||
| A8 |
无风化 |
铅钡 |
0.014602921 |
0.00310062 |
0.022604521 |
%问题一第二小问matlab代码
clear
clc
%高钾玻璃
gjfh=[92.72 0 0 0.94 0.54 2.51 0.2 1.54 0 0 0.36 0 0 0
94.29 0 1.01 0.72 0 1.46 0.29 1.65 0 0 0.15 0 0 0
92.63 0 0 1.07 0 1.98 0.17 3.24 0 0 0.61 0 0 0
95.02 0 0.59 0.62 0 1.32 0.32 1.55 0 0 0.35 0 0 0
96.77 0 0.92 0.21 0 0.81 0.26 0.84 0 0 0 0 0 0
92.35 0 0.74 1.66 0.64 3.5 0.35 0.55 0 0 0.21 0 0 0];
gjfhcfzh=zeros();gjfhcfzb=zeros();gjfhcfzbqwz=zeros();
[m,n]=size(gjfh);
for i=1:m
su=0;
for j=1:n
su=su+gjfh(i,j);
end
gjfhcfzh(i,1)=su;
end
for i=1:m
for j=1:n
gjfhcfzb(i,j)=gjfh(i,j)./gjfhcfzh(i,1);
end
end
for j=1:n
su=0;k=0;
for i=1:m
if gjfh(i,j)>0
k=k+1;
su=su+gjfhcfzb(i,j);
end
end
if su==0
k=1;
end
gjfhcfzbqwz(j)=su./k;
end
gjwfh=[65.88 0 9.67 7.12 1.56 6.44 2.06 2.18 0 0 0.79 0 0 0.36
61.58 0 10.95 7.35 1.77 7.5 2.62 3.27 0 0 0.94 0.06 0 0.47
79.46 0 9.42 0 1.53 3.05 0 0 0 0 1.36 0.07 2.36 0
69.33 0 9.99 6.32 0.87 3.93 1.74 3.87 0 0 1.17 0 0 0.39
59.01 2.86 12.53 8.7 0 6.16 2.88 4.73 0 0 1.27 0 0 0
65.18 2.1 14.52 8.27 0.52 6.18 0.42 1.07 0.11 0 0 0.04 0 0
76.68 0 0 4.71 1.22 6.19 2.37 3.28 1 1.97 1.1 0 0 0
59.81 0 7.68 5.41 1.73 10.05 6.04 2.18 0.35 0.97 4.5 0.12 0 0
61.71 0 12.37 5.87 1.11 5.5 2.16 5.09 1.41 2.86 0.7 0.1 0 0
67.65 0 7.37 0 1.98 11.15 2.39 2.51 0.2 1.38 4.18 0.11 0 0
62.47 3.38 12.28 8.23 0.66 9.23 0.5 0.47 1.62 0 0.16 0 0 0
87.05 0 5.19 2.01 0 4.06 0 0.78 0.25 0 0.66 0 0 0];
gjwfhcfzh=zeros();gjwfhcfzb=zeros();gjwfhcfzbqwz=zeros();
[m,n]=size(gjwfh);
for i=1:m
su=0;
for j=1:n
su=su+gjwfh(i,j);
end
gjwfhcfzh(i,1)=su;
end
for i=1:m
for j=1:n
gjwfhcfzb(i,j)=gjwfh(i,j)./gjwfhcfzh(i,1);
end
end
for j=1:n
su=0;k=0;
for i=1:m
if gjwfh(i,j)>0
k=k+1;
su=su+gjwfhcfzb(i,j);
end
end
if su==0
k=1;
end
gjwfhcfzbqwz(j)=su./k;
end
%铅钡玻璃
qbfh=[17.98 0 0 3.19 0.47 1.87 0.33 1.13 44 14.2 6.34 0.66 0 0
21.35 0 0 5.13 1.45 2.51 0.42 0.75 51.34 0 8.75 0 0 0
29.15 0 0 1.21 0 1.85 0 0.79 41.25 15.45 2.54 0 0 0
25.42 0 0 1.31 0 2.18 0 1.16 45.1 17.3 0 0 0 0
18.46 0 0.44 4.96 2.73 3.33 1.79 0.19 44.12 9.76 7.46 0.47 0 0
25.74 1.22 0 2.27 0.55 1.16 0.23 0.7 47.42 8.64 5.71 0.44 0 0
12.41 0 0 5.24 0.89 2.25 0.76 5.35 59.85 7.29 0 0.64 0 0
24.61 0 0 3.58 1.19 5.25 1.19 1.37 40.24 8.94 8.1 0.39 0.47 0
33.59 0 0.21 3.51 0.71 2.69 0 4.93 25.39 14.61 9.38 0.37 0 0
28.79 0 0 4.58 1.47 5.38 2.74 0.7 34.18 6.1 11.1 0.46 0 0
21.7 0 0 6.4 0.95 3.41 1.39 1.51 44.75 3.26 12.83 0.47 0 0
17.11 0 0 0 1.11 3.65 0 1.34 58.46 0 14.13 1.12 0 0
35.78 0 0.25 0.78 0 1.62 0.47 1.51 46.55 10 0.34 0.22 0 0
39.57 2.22 0.14 0.37 0 1.6 0.32 0.68 41.61 10.83 0.07 0.22 0 0
4.61 0 0 3.19 0 1.11 0 3.14 32.45 30.62 7.56 0.53 0 15.03
16.71 0 0 1.87 0 0.45 0.19 0 70.21 6.69 1.77 0.68 0 0
32.93 1.38 0 0.68 0 2.57 0.29 0.73 49.31 9.79 0.48 0.41 0 0
29.64 0 0 2.93 0.59 3.57 1.33 3.51 42.82 5.35 8.83 0.19 0 0
26.25 0 0 1.11 0 0.5 0 0.88 61.03 7.22 1.16 0.61 0 0
30.39 0 0.34 3.49 0.79 3.52 0.86 3.13 39.35 7.66 8.99 0.24 0 0
53.33 0.8 0.32 2.82 1.54 13.65 1.03 0 15.71 7.31 1.1 0.25 1.31 0
22.28 0 0.32 3.19 1.28 4.15 0 0.83 55.46 7.04 4.24 0.88 0 0
19.79 0 0 1.44 0 0.7 0 10.57 29.53 32.25 3.13 0.45 0 1.96
20.14 0 0 1.48 0 1.34 0 10.41 28.68 31.23 3.59 0.37 0 2.58
36.28 0 1.05 2.34 1.18 5.73 1.86 0.26 47.43 0 3.57 0.19 0 0
3.72 0 0.4 3.01 0 1.18 0 3.6 29.92 35.45 6.04 0.62 0 15.95];
qbfhcfzh=zeros();qbfhcfzb=zeros();qbfhcfzbqwz=zeros();
[m,n]=size(qbfh);
for i=1:m
su=0;
for j=1:n
su=su+qbfh(i,j);
end
qbfhcfzh(i,1)=su;
end
for i=1:m
for j=1:n
qbfhcfzb(i,j)=qbfh(i,j)./qbfhcfzh(i,1);
end
end
for j=1:n
su=0;k=0;
for i=1:m
if qbfh(i,j)>0
k=k+1;
su=su+qbfhcfzb(i,j);
end
end
if su==0
k=1;
end
qbfhcfzbqwz(j)=su./k;
end
qbwfh=[37.36 0 0.71 0 0 5.45 1.51 4.78 9.3 23.55 5.75 0 0 0
65.91 0 0 0.38 0 1.44 0.17 0.16 22.05 5.68 0.42 0 0 0
49.01 2.71 0 1.13 0 1.45 0 0.86 32.92 7.95 0.35 0 0 0
53.79 7.92 0 0.5 0.71 1.42 0 2.99 16.98 11.86 0 0.33 0 0
45.02 0 0 3.12 0.54 4.16 0 0.7 30.61 6.22 6.34 0.23 0 0
50.61 2.31 0 0.63 0 1.9 1.55 1.12 31.9 6.65 0.19 0.2 0 0
51.54 4.66 0.29 0.87 0.61 3.06 0 0.65 25.4 9.23 0.1 0.85 0 0
51.33 5.68 0.35 0 1.16 5.66 0 2.72 20.12 10.88 0 0 0 0
34.34 0 1.41 4.49 0.98 4.35 2.12 0 39.22 10.29 0 0.35 0.4 0
51.26 5.74 0.15 0.79 1.09 3.53 0 2.67 21.88 10.47 0.08 0.35 0 0
54.61 0 0.3 2.08 1.2 6.5 1.27 0.45 23.02 4.19 4.32 0.3 0 0
63.66 3.04 0.11 0.78 1.14 6.06 0 0.54 13.66 8.99 0 0.27 0 0
61.28 2.66 0.11 0.84 0.74 5 0 0.53 15.99 10.96 0 0.23 0 0
65.91 0 0 1.6 0.89 3.11 4.59 0.44 16.55 3.42 1.62 0.3 0 0
55.21 0 0.25 0 1.67 4.79 0 0.77 25.25 10.06 0.2 0.43 0 0
69.71 0 0.21 0.46 0 2.36 1 0.11 19.76 4.88 0.17 0 0 0
68.08 0 0.26 1.34 1 4.7 0.41 0.33 17.14 4.04 1.04 0.12 0.23 0
36.93 0 0 4.24 0.51 3.86 2.74 0 37.74 10.35 1.41 0.48 0.44 0
31.94 0 0 0.47 0 1.59 0 8.46 29.14 26.23 0.14 0.91 0 0
60.74 3.06 0.2 2.14 0 12.69 0.77 0.43 13.61 5.22 0 0.26 0 0
63.3 0.92 0.3 2.98 1.49 14.34 0.81 0.74 12.31 2.03 0.41 0.25 0 0
75.51 0 0.15 0.64 1 2.35 0 0.47 16.16 3.55 0.13 0 0 0
60.12 0 0.23 0.89 0 2.72 0 3.01 17.24 10.34 1.46 0.31 0 3.66];
qbwfhcfzh=zeros();qbwfhcfzb=zeros();qbwfhcfzbqwz=zeros();
[m,n]=size(qbwfh);
for i=1:m
su=0;
for j=1:n
su=su+qbwfh(i,j);
end
qbwfhcfzh(i,1)=su;
end
for i=1:m
for j=1:n
qbwfhcfzb(i,j)=qbwfh(i,j)./qbwfhcfzh(i,1);
end
end
for j=1:n
su=0;k=0;
for i=1:m
if qbwfh(i,j)>0
k=k+1;
su=su+qbwfhcfzb(i,j);
end
end
if su==0
k=1;
end
qbwfhcfzbqwz(j)=su./k;
end
fhfx=zeros();
for i=1:14
if gjfhcfzbqwz(i)>=qbfhcfzbqwz(i)
fhfx(i)=0;
else
fhfx(i)=1;
end
end
wfhfx=zeros();
for i=1:14
if gjwfhcfzbqwz(i)>=qbwfhcfzbqwz(i)
wfhfx(i)=0;
else
wfhfx(i)=1;
end
end
gjfhljh=sum(gjfhcfzbqwz,'all');
gjwfhljh=sum(gjwfhcfzbqwz,'all');
qbfhljh=sum(qbfhcfzbqwz,'all');
qbwfhljh=sum(qbwfhcfzbqwz,'all');
fhgj=zeros();
for i=1:14
fhgj(i)=gjfhcfzbqwz(i)./gjfhljh;
end
wfhgj=zeros();
for i=1:14
wfhgj(i)=gjwfhcfzbqwz(i)./gjwfhljh;
end
fhqb=zeros();
for i=1:14
fhqb(i)=qbfhcfzbqwz(i)./qbfhljh;
end
wfhqb=zeros();
for i=1:14
wfhqb(i)=qbwfhcfzbqwz(i)./qbwfhljh;
end
gjcz=zeros();
for i=1:14
gjcz(i)=wfhgj(i)-fhgj(i);
end
qbcz=zeros();
for i=1:14
qbcz(i)=wfhqb(i)-fhqb(i);
end
%问题二第一小问matlab代码
clear
clc
%高钾玻璃
gjfh=[92.72 0 0 0.94 0.54 2.51 0.2 1.54 0 0 0.36 0 0 0
94.29 0 1.01 0.72 0 1.46 0.29 1.65 0 0 0.15 0 0 0
92.63 0 0 1.07 0 1.98 0.17 3.24 0 0 0.61 0 0 0
95.02 0 0.59 0.62 0 1.32 0.32 1.55 0 0 0.35 0 0 0
96.77 0 0.92 0.21 0 0.81 0.26 0.84 0 0 0 0 0 0
92.35 0 0.74 1.66 0.64 3.5 0.35 0.55 0 0 0.21 0 0 0];
gjfhcfzh=zeros();gjfhcfzb=zeros();gjfhcfzbqwz=zeros();
[m,n]=size(gjfh);
for i=1:m
sum=0;
for j=1:n
sum=sum+gjfh(i,j);
end
gjfhcfzh(i,1)=sum;
end
for i=1:m
for j=1:n
gjfhcfzb(i,j)=gjfh(i,j)./gjfhcfzh(i,1);
end
end
for j=1:n
sum=0;k=0;
for i=1:m
if gjfh(i,j)>0
k=k+1;
sum=sum+gjfhcfzb(i,j);
end
end
gjfhcfzbqwz(j)=sum./k;
end
gjwfh=[65.88 0 9.67 7.12 1.56 6.44 2.06 2.18 0 0 0.79 0 0 0.36
61.58 0 10.95 7.35 1.77 7.5 2.62 3.27 0 0 0.94 0.06 0 0.47
79.46 0 9.42 0 1.53 3.05 0 0 0 0 1.36 0.07 2.36 0
69.33 0 9.99 6.32 0.87 3.93 1.74 3.87 0 0 1.17 0 0 0.39
59.01 2.86 12.53 8.7 0 6.16 2.88 4.73 0 0 1.27 0 0 0
65.18 2.1 14.52 8.27 0.52 6.18 0.42 1.07 0.11 0 0 0.04 0 0
76.68 0 0 4.71 1.22 6.19 2.37 3.28 1 1.97 1.1 0 0 0
59.81 0 7.68 5.41 1.73 10.05 6.04 2.18 0.35 0.97 4.5 0.12 0 0
61.71 0 12.37 5.87 1.11 5.5 2.16 5.09 1.41 2.86 0.7 0.1 0 0
67.65 0 7.37 0 1.98 11.15 2.39 2.51 0.2 1.38 4.18 0.11 0 0
62.47 3.38 12.28 8.23 0.66 9.23 0.5 0.47 1.62 0 0.16 0 0 0
87.05 0 5.19 2.01 0 4.06 0 0.78 0.25 0 0.66 0 0 0];
gjwfhcfzh=zeros();gjwfhcfzb=zeros();gjwfhcfzbqwz=zeros();
[m,n]=size(gjwfh);
for i=1:m
sum=0;
for j=1:n
sum=sum+gjwfh(i,j);
end
gjwfhcfzh(i,1)=sum;
end
for i=1:m
for j=1:n
gjwfhcfzb(i,j)=gjwfh(i,j)./gjwfhcfzh(i,1);
end
end
for j=1:n
sum=0;k=0;
for i=1:m
if gjwfh(i,j)>0
k=k+1;
sum=sum+gjwfhcfzb(i,j);
end
end
gjwfhcfzbqwz(j)=sum./k;
end
%铅钡玻璃
qbfh=[17.98 0 0 3.19 0.47 1.87 0.33 1.13 44 14.2 6.34 0.66 0 0
21.35 0 0 5.13 1.45 2.51 0.42 0.75 51.34 0 8.75 0 0 0
29.15 0 0 1.21 0 1.85 0 0.79 41.25 15.45 2.54 0 0 0
25.42 0 0 1.31 0 2.18 0 1.16 45.1 17.3 0 0 0 0
18.46 0 0.44 4.96 2.73 3.33 1.79 0.19 44.12 9.76 7.46 0.47 0 0
25.74 1.22 0 2.27 0.55 1.16 0.23 0.7 47.42 8.64 5.71 0.44 0 0
12.41 0 0 5.24 0.89 2.25 0.76 5.35 59.85 7.29 0 0.64 0 0
24.61 0 0 3.58 1.19 5.25 1.19 1.37 40.24 8.94 8.1 0.39 0.47 0
33.59 0 0.21 3.51 0.71 2.69 0 4.93 25.39 14.61 9.38 0.37 0 0
28.79 0 0 4.58 1.47 5.38 2.74 0.7 34.18 6.1 11.1 0.46 0 0
21.7 0 0 6.4 0.95 3.41 1.39 1.51 44.75 3.26 12.83 0.47 0 0
17.11 0 0 0 1.11 3.65 0 1.34 58.46 0 14.13 1.12 0 0
35.78 0 0.25 0.78 0 1.62 0.47 1.51 46.55 10 0.34 0.22 0 0
39.57 2.22 0.14 0.37 0 1.6 0.32 0.68 41.61 10.83 0.07 0.22 0 0
4.61 0 0 3.19 0 1.11 0 3.14 32.45 30.62 7.56 0.53 0 15.03
16.71 0 0 1.87 0 0.45 0.19 0 70.21 6.69 1.77 0.68 0 0
32.93 1.38 0 0.68 0 2.57 0.29 0.73 49.31 9.79 0.48 0.41 0 0
29.64 0 0 2.93 0.59 3.57 1.33 3.51 42.82 5.35 8.83 0.19 0 0
26.25 0 0 1.11 0 0.5 0 0.88 61.03 7.22 1.16 0.61 0 0
30.39 0 0.34 3.49 0.79 3.52 0.86 3.13 39.35 7.66 8.99 0.24 0 0
53.33 0.8 0.32 2.82 1.54 13.65 1.03 0 15.71 7.31 1.1 0.25 1.31 0
22.28 0 0.32 3.19 1.28 4.15 0 0.83 55.46 7.04 4.24 0.88 0 0
19.79 0 0 1.44 0 0.7 0 10.57 29.53 32.25 3.13 0.45 0 1.96
20.14 0 0 1.48 0 1.34 0 10.41 28.68 31.23 3.59 0.37 0 2.58
36.28 0 1.05 2.34 1.18 5.73 1.86 0.26 47.43 0 3.57 0.19 0 0
3.72 0 0.4 3.01 0 1.18 0 3.6 29.92 35.45 6.04 0.62 0 15.95];
qbfhcfzh=zeros();qbfhcfzb=zeros();qbfhcfzbqwz=zeros();
[m,n]=size(qbfh);
for i=1:m
sum=0;
for j=1:n
sum=sum+qbfh(i,j);
end
qbfhcfzh(i,1)=sum;
end
for i=1:m
for j=1:n
qbfhcfzb(i,j)=qbfh(i,j)./qbfhcfzh(i,1);
end
end
for j=1:n
sum=0;k=0;
for i=1:m
if qbfh(i,j)>0
k=k+1;
sum=sum+qbfhcfzb(i,j);
end
end
qbfhcfzbqwz(j)=sum./k;
end
qbwfh=[37.36 0 0.71 0 0 5.45 1.51 4.78 9.3 23.55 5.75 0 0 0
65.91 0 0 0.38 0 1.44 0.17 0.16 22.05 5.68 0.42 0 0 0
49.01 2.71 0 1.13 0 1.45 0 0.86 32.92 7.95 0.35 0 0 0
53.79 7.92 0 0.5 0.71 1.42 0 2.99 16.98 11.86 0 0.33 0 0
45.02 0 0 3.12 0.54 4.16 0 0.7 30.61 6.22 6.34 0.23 0 0
50.61 2.31 0 0.63 0 1.9 1.55 1.12 31.9 6.65 0.19 0.2 0 0
51.54 4.66 0.29 0.87 0.61 3.06 0 0.65 25.4 9.23 0.1 0.85 0 0
51.33 5.68 0.35 0 1.16 5.66 0 2.72 20.12 10.88 0 0 0 0
34.34 0 1.41 4.49 0.98 4.35 2.12 0 39.22 10.29 0 0.35 0.4 0
51.26 5.74 0.15 0.79 1.09 3.53 0 2.67 21.88 10.47 0.08 0.35 0 0
54.61 0 0.3 2.08 1.2 6.5 1.27 0.45 23.02 4.19 4.32 0.3 0 0
63.66 3.04 0.11 0.78 1.14 6.06 0 0.54 13.66 8.99 0 0.27 0 0
61.28 2.66 0.11 0.84 0.74 5 0 0.53 15.99 10.96 0 0.23 0 0
65.91 0 0 1.6 0.89 3.11 4.59 0.44 16.55 3.42 1.62 0.3 0 0
55.21 0 0.25 0 1.67 4.79 0 0.77 25.25 10.06 0.2 0.43 0 0
69.71 0 0.21 0.46 0 2.36 1 0.11 19.76 4.88 0.17 0 0 0
68.08 0 0.26 1.34 1 4.7 0.41 0.33 17.14 4.04 1.04 0.12 0.23 0
36.93 0 0 4.24 0.51 3.86 2.74 0 37.74 10.35 1.41 0.48 0.44 0
31.94 0 0 0.47 0 1.59 0 8.46 29.14 26.23 0.14 0.91 0 0
60.74 3.06 0.2 2.14 0 12.69 0.77 0.43 13.61 5.22 0 0.26 0 0
63.3 0.92 0.3 2.98 1.49 14.34 0.81 0.74 12.31 2.03 0.41 0.25 0 0
75.51 0 0.15 0.64 1 2.35 0 0.47 16.16 3.55 0.13 0 0 0
60.12 0 0.23 0.89 0 2.72 0 3.01 17.24 10.34 1.46 0.31 0 3.66];
qbwfhcfzh=zeros();qbwfhcfzb=zeros();qbwfhcfzbqwz=zeros();
[m,n]=size(qbwfh);
for i=1:m
sum=0;
for j=1:n
sum=sum+qbwfh(i,j);
end
qbwfhcfzh(i,1)=sum;
end
for i=1:m
for j=1:n
qbwfhcfzb(i,j)=qbwfh(i,j)./qbwfhcfzh(i,1);
end
end
for j=1:n
sum=0;k=0;
for i=1:m
if qbwfh(i,j)>0
k=k+1;
sum=sum+qbwfhcfzb(i,j);
end
end
qbwfhcfzbqwz(j)=sum./k;
end
fhfx=zeros();
for i=1:14
if gjfhcfzbqwz(i)>=qbfhcfzbqwz(i)
fhfx(i)=0;
else
fhfx(i)=1;
end
end
wfhfx=zeros();
for i=1:14
if gjwfhcfzbqwz(i)>=qbwfhcfzbqwz(i)
wfhfx(i)=0;
else
wfhfx(i)=1;
end
end
%问题二第二小问的matlab代码
%初始数据归一化处理
clear
clc
z=[69.33 0 9.99 6.32 0.87 3.93 1.74 3.87 0 0 1.17 0 0 0.39
36.28 0 1.05 2.34 1.18 5.73 1.86 0.26 47.43 0 3.57 0.19 0 0
87.05 0 5.19 2.01 0 4.06 0 0.78 0.25 0 0.66 0 0 0
61.71 0 12.37 5.87 1.11 5.5 2.16 5.09 1.41 2.86 0.7 0.1 0 0
65.88 0 9.67 7.12 1.56 6.44 2.06 2.18 0 0 0.79 0 0 0.36
61.58 0 10.95 7.35 1.77 7.5 2.62 3.27 0 0 0.94 0.06 0 0.47
67.65 0 7.37 0 1.98 11.15 2.39 2.51 0.2 1.38 4.18 0.11 0 0
59.81 0 7.68 5.41 1.73 10.05 6.04 2.18 0.35 0.97 4.5 0.12 0 0
92.63 0 0 1.07 0 1.98 0.17 3.24 0 0 0.61 0 0 0
20.14 0 0 1.48 0 1.34 0 10.41 28.68 31.23 3.59 0.37 0 2.58
4.61 0 0 3.19 0 1.11 0 3.14 32.45 30.62 7.56 0.53 0 15.03
95.02 0 0.59 0.62 0 1.32 0.32 1.55 0 0 0.35 0 0 0
96.77 0 0.92 0.21 0 0.81 0.26 0.84 0 0 0 0 0 0
33.59 0 0.21 3.51 0.71 2.69 0 4.93 25.39 14.61 9.38 0.37 0 0
94.29 0 1.01 0.72 0 1.46 0.29 1.65 0 0 0.15 0 0 0
59.01 2.86 12.53 8.7 0 6.16 2.88 4.73 0 0 1.27 0 0 0
62.47 3.38 12.28 8.23 0.66 9.23 0.5 0.47 1.62 0 0.16 0 0 0
65.18 2.1 14.52 8.27 0.52 6.18 0.42 1.07 0.11 0 0 0.04 0 0
79.46 0 9.42 0 1.53 3.05 0 0 0 0 1.36 0.07 2.36 0
29.64 0 0 2.93 0.59 3.57 1.33 3.51 42.82 5.35 8.83 0.19 0 0
53.33 0.8 0.32 2.82 1.54 13.65 1.03 0 15.71 7.31 1.1 0.25 1.31 0
76.68 0 0 4.71 1.22 6.19 2.37 3.28 1 1.97 1.1 0 0 0
92.35 0 0.74 1.66 0.64 3.5 0.35 0.55 0 0 0.21 0 0 0
28.79 0 0 4.58 1.47 5.38 2.74 0.7 34.18 6.1 11.1 0.46 0 0
31.94 0 0 0.47 0 1.59 0 8.46 29.14 26.23 0.14 0.91 0 0
50.61 2.31 0 0.63 0 1.9 1.55 1.12 31.9 6.65 0.19 0.2 0 0
19.79 0 0 1.44 0 0.7 0 10.57 29.53 32.25 3.13 0.45 0 1.96
3.72 0 0.4 3.01 0 1.18 0 3.6 29.92 35.45 6.04 0.62 0 15.95
92.72 0 0 0.94 0.54 2.51 0.2 1.54 0 0 0.36 0 0 0
17.98 0 0 3.19 0.47 1.87 0.33 1.13 44 14.2 6.34 0.66 0 0
37.36 0 0.71 0 0 5.45 1.51 4.78 9.3 23.55 5.75 0 0 0
53.79 7.92 0 0.5 0.71 1.42 0 2.99 16.98 11.86 0 0.33 0 0
68.08 0 0.26 1.34 1 4.7 0.41 0.33 17.14 4.04 1.04 0.12 0.23 0
65.91 0 0 1.6 0.89 3.11 4.59 0.44 16.55 3.42 1.62 0.3 0 0
69.71 0 0.21 0.46 0 2.36 1 0.11 19.76 4.88 0.17 0 0 0
75.51 0 0.15 0.64 1 2.35 0 0.47 16.16 3.55 0.13 0 0 0
35.78 0 0.25 0.78 0 1.62 0.47 1.51 46.55 10 0.34 0.22 0 0
65.91 0 0 0.38 0 1.44 0.17 0.16 22.05 5.68 0.42 0 0 0
39.57 2.22 0.14 0.37 0 1.6 0.32 0.68 41.61 10.83 0.07 0.22 0 0
60.12 0 0.23 0.89 0 2.72 0 3.01 17.24 10.34 1.46 0.31 0 3.66
32.93 1.38 0 0.68 0 2.57 0.29 0.73 49.31 9.79 0.48 0.41 0 0
26.25 0 0 1.11 0 0.5 0 0.88 61.03 7.22 1.16 0.61 0 0
16.71 0 0 1.87 0 0.45 0.19 0 70.21 6.69 1.77 0.68 0 0
18.46 0 0.44 4.96 2.73 3.33 1.79 0.19 44.12 9.76 7.46 0.47 0 0
63.3 0.92 0.3 2.98 1.49 14.34 0.81 0.74 12.31 2.03 0.41 0.25 0 0
34.34 0 1.41 4.49 0.98 4.35 2.12 0 39.22 10.29 0 0.35 0.4 0
12.41 0 0 5.24 0.89 2.25 0.76 5.35 59.85 7.29 0 0.64 0 0
21.7 0 0 6.4 0.95 3.41 1.39 1.51 44.75 3.26 12.83 0.47 0 0
36.93 0 0 4.24 0.51 3.86 2.74 0 37.74 10.35 1.41 0.48 0.44 0
51.26 5.74 0.15 0.79 1.09 3.53 0 2.67 21.88 10.47 0.08 0.35 0 0
51.33 5.68 0.35 0 1.16 5.66 0 2.72 20.12 10.88 0 0 0 0
60.74 3.06 0.2 2.14 0 12.69 0.77 0.43 13.61 5.22 0 0.26 0 0
61.28 2.66 0.11 0.84 0.74 5 0 0.53 15.99 10.96 0 0.23 0 0
55.21 0 0.25 0 1.67 4.79 0 0.77 25.25 10.06 0.2 0.43 0 0
51.54 4.66 0.29 0.87 0.61 3.06 0 0.65 25.4 9.23 0.1 0.85 0 0
54.61 0 0.3 2.08 1.2 6.5 1.27 0.45 23.02 4.19 4.32 0.3 0 0
45.02 0 0 3.12 0.54 4.16 0 0.7 30.61 6.22 6.34 0.23 0 0
24.61 0 0 3.58 1.19 5.25 1.19 1.37 40.24 8.94 8.1 0.39 0.47 0
21.35 0 0 5.13 1.45 2.51 0.42 0.75 51.34 0 8.75 0 0 0
25.74 1.22 0 2.27 0.55 1.16 0.23 0.7 47.42 8.64 5.71 0.44 0 0
63.66 3.04 0.11 0.78 1.14 6.06 0 0.54 13.66 8.99 0 0.27 0 0
22.28 0 0.32 3.19 1.28 4.15 0 0.83 55.46 7.04 4.24 0.88 0 0
17.11 0 0 0 1.11 3.65 0 1.34 58.46 0 14.13 1.12 0 0
49.01 2.71 0 1.13 0 1.45 0 0.86 32.92 7.95 0.35 0 0 0
29.15 0 0 1.21 0 1.85 0 0.79 41.25 15.45 2.54 0 0 0
25.42 0 0 1.31 0 2.18 0 1.16 45.1 17.3 0 0 0 0
30.39 0 0.34 3.49 0.79 3.52 0.86 3.13 39.35 7.66 8.99 0.24 0 0];
h=[97.61 99.89 100 98.88 96.06 96.51 98.92 98.84 99.7 99.82 98.24 99.77 99.81 95.39 99.57 98.14 99 98.41 97.25 98.76 99.17 98.52 100 95.5 98.88 97.06 99.82 99.89 98.81 90.17 88.41 96.5 98.69 98.43 98.66 99.96 97.52 96.21 97.63 99.98 98.57 98.76 98.57 93.71 99.88 97.95 94.68 96.67 98.7 98.01 97.9 99.12 98.34 98.63 97.26 98.24 96.94 95.33 91.7 94.08 98.25 99.67 96.92 96.38 92.24 92.47 98.76]';
gui=zeros();
for i=1:67
for j=1:14
gui(i,j)=z(i,j)./h(i);
end
end
clear
clc
yl1=[0.028691099 0.007329843 0.357905759 0
0.003659754 0.012531884 0.487967173 0];
yl2=[0.018620483 0.002602863 0.474822305 0];
yl3=[0.012927524 0.004580619 0.234324104 0
0 0.007220961 0.315762327 0];
yl4=[0 0.030984456 0.175958549 0];
yl5=[0.017079516 0.054066282 0.10519172 0
0.004154423 0.003343804 0.173675144 0.00233053
0.008109732 0.007408891 0.123247897 0
0 0.027242118 0.223242526 0
0 0.027783453 0.205515832 0
0.007768362 0.004338176 0.137308313 0
0 0.005389465 0.162599146 0
0 0.007806955 0.2560073 0
0 0.006683117 0.261155665 0
0 0.005496183 0.139033079 0];
yl6=[0.021643696 0 0.400408372 0.004083716
0.027760892 0 0.382370821 0.004457953];
yl7=[0 0.008564614 0.447202949 0
0 0.012544609 0.487725749 0];
yl8=[0 0.051682566 0.266170458 0
0.008027038 0.056506126 0.632129278 0
0.014378815 0.015620151 0.462915072 0
0.012482954 0.014371132 0.422112661 0.004930242
0.004580153 0.008178844 0.559869138 0
0.002444728 0.007440476 0.504039116 0
0 0.008327481 0.55643624 0
0 0.013825836 0.603177879 0];
yl9=[0.019101483 0.002027532 0.470814214 0];
yl10=[0.004819524 0.015484003 0.477337982 0
0.003277681 0.006965072 0.426200963 0
0.002942072 0.007405904 0.500253627 0
0 0.00891049 0.617962738 0];
yl11=[0 0.104287718 0.287317171 0
0 0.031962541 0.330313518 0
0 0.105890603 0.295832498 0
0 0.036039644 0.299529482 0];
yl12=[0 0.008923013 0.34156464 0];
yl13=[0.015969503 0.011539254 0.328662683 0];
yl14=[0.01013582 0.00111494 0.200283803 0
0.001766968 0.001663029 0.229186155 0];
yl15=[0 0.004701881 0.161664666 0
0 0.030106021 0.172434487 0];
yl16=[0 0.085558252 0.294700647 0
0.046632124 0.004470182 0.168139795 0];
yl17=[0 0.0078 0.0025 0
0.02184466 0.051476537 0.014259709 0
0.02144493 0.022694149 0 0
0.027147446 0.033882499 0 0
0.024160938 0.02537404 0.002021836 0
0.061108863 0.022055848 0.003541076 0
0.024056029 0.033292732 0.010150223 0];
yl18=[0 0 0 0.024267352];
yl19=[0.001705115 0.032497492 0 0
0.003207377 0.015535732 0 0
0.002604949 0.00841599 0 0
0.002912524 0.016571256 0 0
0.0035 0.0055 0 0
0.002024087 0.015585467 0 0];
yl20=[0.017826042 0.039647577 0 0];
yl21=[0.029345832 0.048196454 0 0
0.004267859 0.010872879 0.001117773 0];
yl22=[0.005050505 0.004747475 0.016363636 0];
fl=zeros();
for j=1:4
su=0;[m,n]=size(yl1);
for i=1:m
su=su+yl1(i,j);
end
fl(1,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl2);
for i=1:m
su=su+yl2(i,j);
end
fl(2,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl3);
for i=1:m
su=su+yl3(i,j);
end
fl(3,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl4);
for i=1:m
su=su+yl4(i,j);
end
fl(4,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl5);
for i=1:m
su=su+yl5(i,j);
end
fl(5,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl6);
for i=1:m
su=su+yl6(i,j);
end
fl(6,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl7);
for i=1:m
su=su+yl7(i,j);
end
fl(7,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl8);
for i=1:m
su=su+yl8(i,j);
end
fl(8,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl9);
for i=1:m
su=su+yl9(i,j);
end
fl(9,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl10);
for i=1:m
su=su+yl10(i,j);
end
fl(10,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl11);
for i=1:m
su=su+yl11(i,j);
end
fl(11,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl12);
for i=1:m
su=su+yl12(i,j);
end
fl(12,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl13);
for i=1:m
su=su+yl13(i,j);
end
fl(13,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl14);
for i=1:m
su=su+yl14(i,j);
end
fl(14,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl15);
for i=1:m
su=su+yl15(i,j);
end
fl(15,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl16);
for i=1:m
su=su+yl16(i,j);
end
fl(16,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl17);
for i=1:m
su=su+yl17(i,j);
end
fl(17,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl18);
for i=1:m
su=su+yl18(i,j);
end
fl(18,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl19);
for i=1:m
su=su+yl19(i,j);
end
fl(19,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl20);
for i=1:m
su=su+yl20(i,j);
end
fl(20,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl21);
for i=1:m
su=su+yl21(i,j);
end
fl(21,j)=su./m;
end
for j=1:4
su=0;[m,n]=size(yl22);
for i=1:m
su=su+yl22(i,j);
end
fl(22,j)=su./m;
end
%问题四的matlab代码
%初始数据归一化处理
clear
clc
z=[69.33 0 9.99 6.32 0.87 3.93 1.74 3.87 0 0 1.17 0 0 0.39
36.28 0 1.05 2.34 1.18 5.73 1.86 0.26 47.43 0 3.57 0.19 0 0
87.05 0 5.19 2.01 0 4.06 0 0.78 0.25 0 0.66 0 0 0
61.71 0 12.37 5.87 1.11 5.5 2.16 5.09 1.41 2.86 0.7 0.1 0 0
65.88 0 9.67 7.12 1.56 6.44 2.06 2.18 0 0 0.79 0 0 0.36
61.58 0 10.95 7.35 1.77 7.5 2.62 3.27 0 0 0.94 0.06 0 0.47
67.65 0 7.37 0 1.98 11.15 2.39 2.51 0.2 1.38 4.18 0.11 0 0
59.81 0 7.68 5.41 1.73 10.05 6.04 2.18 0.35 0.97 4.5 0.12 0 0
92.63 0 0 1.07 0 1.98 0.17 3.24 0 0 0.61 0 0 0
20.14 0 0 1.48 0 1.34 0 10.41 28.68 31.23 3.59 0.37 0 2.58
4.61 0 0 3.19 0 1.11 0 3.14 32.45 30.62 7.56 0.53 0 15.03
95.02 0 0.59 0.62 0 1.32 0.32 1.55 0 0 0.35 0 0 0
96.77 0 0.92 0.21 0 0.81 0.26 0.84 0 0 0 0 0 0
33.59 0 0.21 3.51 0.71 2.69 0 4.93 25.39 14.61 9.38 0.37 0 0
94.29 0 1.01 0.72 0 1.46 0.29 1.65 0 0 0.15 0 0 0
59.01 2.86 12.53 8.7 0 6.16 2.88 4.73 0 0 1.27 0 0 0
62.47 3.38 12.28 8.23 0.66 9.23 0.5 0.47 1.62 0 0.16 0 0 0
65.18 2.1 14.52 8.27 0.52 6.18 0.42 1.07 0.11 0 0 0.04 0 0
79.46 0 9.42 0 1.53 3.05 0 0 0 0 1.36 0.07 2.36 0
29.64 0 0 2.93 0.59 3.57 1.33 3.51 42.82 5.35 8.83 0.19 0 0
53.33 0.8 0.32 2.82 1.54 13.65 1.03 0 15.71 7.31 1.1 0.25 1.31 0
76.68 0 0 4.71 1.22 6.19 2.37 3.28 1 1.97 1.1 0 0 0
92.35 0 0.74 1.66 0.64 3.5 0.35 0.55 0 0 0.21 0 0 0
28.79 0 0 4.58 1.47 5.38 2.74 0.7 34.18 6.1 11.1 0.46 0 0
31.94 0 0 0.47 0 1.59 0 8.46 29.14 26.23 0.14 0.91 0 0
50.61 2.31 0 0.63 0 1.9 1.55 1.12 31.9 6.65 0.19 0.2 0 0
19.79 0 0 1.44 0 0.7 0 10.57 29.53 32.25 3.13 0.45 0 1.96
3.72 0 0.4 3.01 0 1.18 0 3.6 29.92 35.45 6.04 0.62 0 15.95
92.72 0 0 0.94 0.54 2.51 0.2 1.54 0 0 0.36 0 0 0
17.98 0 0 3.19 0.47 1.87 0.33 1.13 44 14.2 6.34 0.66 0 0
37.36 0 0.71 0 0 5.45 1.51 4.78 9.3 23.55 5.75 0 0 0
53.79 7.92 0 0.5 0.71 1.42 0 2.99 16.98 11.86 0 0.33 0 0
68.08 0 0.26 1.34 1 4.7 0.41 0.33 17.14 4.04 1.04 0.12 0.23 0
65.91 0 0 1.6 0.89 3.11 4.59 0.44 16.55 3.42 1.62 0.3 0 0
69.71 0 0.21 0.46 0 2.36 1 0.11 19.76 4.88 0.17 0 0 0
75.51 0 0.15 0.64 1 2.35 0 0.47 16.16 3.55 0.13 0 0 0
35.78 0 0.25 0.78 0 1.62 0.47 1.51 46.55 10 0.34 0.22 0 0
65.91 0 0 0.38 0 1.44 0.17 0.16 22.05 5.68 0.42 0 0 0
39.57 2.22 0.14 0.37 0 1.6 0.32 0.68 41.61 10.83 0.07 0.22 0 0
60.12 0 0.23 0.89 0 2.72 0 3.01 17.24 10.34 1.46 0.31 0 3.66
32.93 1.38 0 0.68 0 2.57 0.29 0.73 49.31 9.79 0.48 0.41 0 0
26.25 0 0 1.11 0 0.5 0 0.88 61.03 7.22 1.16 0.61 0 0
16.71 0 0 1.87 0 0.45 0.19 0 70.21 6.69 1.77 0.68 0 0
18.46 0 0.44 4.96 2.73 3.33 1.79 0.19 44.12 9.76 7.46 0.47 0 0
63.3 0.92 0.3 2.98 1.49 14.34 0.81 0.74 12.31 2.03 0.41 0.25 0 0
34.34 0 1.41 4.49 0.98 4.35 2.12 0 39.22 10.29 0 0.35 0.4 0
12.41 0 0 5.24 0.89 2.25 0.76 5.35 59.85 7.29 0 0.64 0 0
21.7 0 0 6.4 0.95 3.41 1.39 1.51 44.75 3.26 12.83 0.47 0 0
36.93 0 0 4.24 0.51 3.86 2.74 0 37.74 10.35 1.41 0.48 0.44 0
51.26 5.74 0.15 0.79 1.09 3.53 0 2.67 21.88 10.47 0.08 0.35 0 0
51.33 5.68 0.35 0 1.16 5.66 0 2.72 20.12 10.88 0 0 0 0
60.74 3.06 0.2 2.14 0 12.69 0.77 0.43 13.61 5.22 0 0.26 0 0
61.28 2.66 0.11 0.84 0.74 5 0 0.53 15.99 10.96 0 0.23 0 0
55.21 0 0.25 0 1.67 4.79 0 0.77 25.25 10.06 0.2 0.43 0 0
51.54 4.66 0.29 0.87 0.61 3.06 0 0.65 25.4 9.23 0.1 0.85 0 0
54.61 0 0.3 2.08 1.2 6.5 1.27 0.45 23.02 4.19 4.32 0.3 0 0
45.02 0 0 3.12 0.54 4.16 0 0.7 30.61 6.22 6.34 0.23 0 0
24.61 0 0 3.58 1.19 5.25 1.19 1.37 40.24 8.94 8.1 0.39 0.47 0
21.35 0 0 5.13 1.45 2.51 0.42 0.75 51.34 0 8.75 0 0 0
25.74 1.22 0 2.27 0.55 1.16 0.23 0.7 47.42 8.64 5.71 0.44 0 0
63.66 3.04 0.11 0.78 1.14 6.06 0 0.54 13.66 8.99 0 0.27 0 0
22.28 0 0.32 3.19 1.28 4.15 0 0.83 55.46 7.04 4.24 0.88 0 0
17.11 0 0 0 1.11 3.65 0 1.34 58.46 0 14.13 1.12 0 0
49.01 2.71 0 1.13 0 1.45 0 0.86 32.92 7.95 0.35 0 0 0
29.15 0 0 1.21 0 1.85 0 0.79 41.25 15.45 2.54 0 0 0
25.42 0 0 1.31 0 2.18 0 1.16 45.1 17.3 0 0 0 0
30.39 0 0.34 3.49 0.79 3.52 0.86 3.13 39.35 7.66 8.99 0.24 0 0];
h=[97.61 99.89 100 98.88 96.06 96.51 98.92 98.84 99.7 99.82 98.24 99.77 99.81 95.39 99.57 98.14 99 98.41 97.25 98.76 99.17 98.52 100 95.5 98.88 97.06 99.82 99.89 98.81 90.17 88.41 96.5 98.69 98.43 98.66 99.96 97.52 96.21 97.63 99.98 98.57 98.76 98.57 93.71 99.88 97.95 94.68 96.67 98.7 98.01 97.9 99.12 98.34 98.63 97.26 98.24 96.94 95.33 91.7 94.08 98.25 99.67 96.92 96.38 92.24 92.47 98.76]';
gui=zeros();
for i=1:67
for j=1:14
gui(i,j)=z(i,j)./h(i);
end
end
clear
clc
lb1=[0.018620483 0.002602863 0.474822305 0
0.028691099 0.007329843 0.357905759 0
0.003659754 0.012531884 0.487967173 0];
lb2=[0.017079516 0.054066282 0.10519172 0
0 0.030984456 0.175958549 0
0.004154423 0.003343804 0.173675144 0.00233053
0.008109732 0.007408891 0.123247897 0
0.021643696 0 0.400408372 0.004083716
0.027760892 0 0.382370821 0.004457953
0 0.027242118 0.223242526 0
0 0.027783453 0.205515832 0
0.007768362 0.004338176 0.137308313 0
0 0.005389465 0.162599146 0
0 0.007806955 0.2560073 0
0 0.006683117 0.261155665 0
0.012927524 0.004580619 0.234324104 0
0 0.007220961 0.315762327 0
0 0.005496183 0.139033079 0];
lb3=[0 0.104287718 0.287317171 0
0 0.031962541 0.330313518 0
0 0.051682566 0.266170458 0
0 0.105890603 0.295832498 0
0 0.036039644 0.299529482 0
0.004819524 0.015484003 0.477337982 0
0.003277681 0.006965072 0.426200963 0
0.002942072 0.007405904 0.500253627 0
0 0.00891049 0.617962738 0
0.019101483 0.002027532 0.470814214 0
0.008027038 0.056506126 0.632129278 0
0.014378815 0.015620151 0.462915072 0
0.012482954 0.014371132 0.422112661 0.004930242
0.004580153 0.008178844 0.559869138 0
0.002444728 0.007440476 0.504039116 0
0 0.008327481 0.55643624 0
0 0.013825836 0.603177879 0
0 0.008564614 0.447202949 0
0 0.012544609 0.487725749 0];
lb4=[0 0.085558252 0.294700647 0
0.015969503 0.011539254 0.328662683 0
0.046632124 0.004470182 0.168139795 0
0.01013582 0.00111494 0.200283803 0
0 0.004701881 0.161664666 0
0.001766968 0.001663029 0.229186155 0
0 0.030106021 0.172434487 0
0 0.008923013 0.34156464 0];
lb5=[0 0.0078 0.0025 0
0.02184466 0.051476537 0.014259709 0
0.02144493 0.022694149 0 0
0.027147446 0.033882499 0 0
0.024160938 0.02537404 0.002021836 0
0.061108863 0.022055848 0.003541076 0
0 0 0 0.024267352
0.024056029 0.033292732 0.010150223 0];
lb6=[0.001705115 0.032497492 0 0
0.003207377 0.015535732 0 0
0.002604949 0.00841599 0 0
0.002912524 0.016571256 0 0
0.0035 0.0055 0 0
0.002024087 0.015585467 0 0];
lb7=[0.017826042 0.039647577 0 0
0.029345832 0.048196454 0 0
0.005050505 0.004747475 0.016363636 0
0.004267859 0.010872879 0.001117773 0];
glb=zeros();
for j=1:4
[m,n]=size(lb1);su=0;
for i=1:m
su=su+lb1(i,j);
end
glb(1,j)=su./m;
end
for j=1:4
[m,n]=size(lb2);su=0;
for i=1:m
su=su+lb2(i,j);
end
glb(2,j)=su./m;
end
for j=1:4
[m,n]=size(lb3);su=0;
for i=1:m
su=su+lb3(i,j);
end
glb(3,j)=su./m;
end
for j=1:4
[m,n]=size(lb4);su=0;
for i=1:m
su=su+lb4(i,j);
end
glb(4,j)=su./m;
end
for j=1:4
[m,n]=size(lb5);su=0;
for i=1:m
su=su+lb5(i,j);
end
glb(5,j)=su./m;
end
for j=1:4
[m,n]=size(lb6);su=0;
for i=1:m
su=su+lb6(i,j);
end
glb(6,j)=su./m;
end
for j=1:4
[m,n]=size(lb7);su=0;
for i=1:m
su=su+lb7(i,j);
end
glb(7,j)=su./m;
end