Mathematical Modeling and Mathematics Experiment 4th Edition
Mathematical Modeling and Mathematics Experiment Chapter 2 Zhao Jing Danqi Answers to Exercises
Mathematical Modeling and Mathematics Experiment Higher Education Press Answers and Analysis
Chapter 1 Introduction to Mathematical Modeling
1.1 About Mathematical Modeling
1.2 Examples of Mathematical Modeling: Population Forecast Problems
1.3 Methods of Writing Mathematical Modeling Papers
1.4 Answers to Exercises
Chapter 2 Getting Started
with MATLAB 2.1 MATLAB Entry and Operation Methods
2.2 Variables and Functions
2.3 Arrays And matrix
2.4 MATLAB programming
2.5 MATLAB drawing
2.6 answers to
the exercises Chapter 3 linear programming
3.1 linear programming model
3.2 linear programming examples and programming solutions
3.3 modeling cases: investment returns and risks
3.4 exercises
Chapter 4 nonlinear programming
4.1 unconstrained Mathematical models of optimization and nonlinear programming
4.2 Examples and programming solutions of nonlinear programming
4.3 Modeling case: steel tube ordering and transportation optimization model
4.4 Answers to exercises
Chapter 5 Network optimization
5.1 Basic concepts of graph theory
5.2
Shortest path problem and its algorithm 5.3 Shortest Application of Road
5.4 Matching and Covering
5.5 Chinese Postman Problem
5.6 Salesman Problem
5.7 Minimum Spanning Tree Problem
5.8 Modeling Case: Best Disaster Inspection Route
5.9 Exercise Answer
Chapter 6 Differential Equations and Difference Equations
6.1 Differential Equation Model
6.2 Numerical solutions of differential equations
6.3 Differential equations solved by MATLAB
6.4 Differential equation models and solutions
6.5 Modeling case: Mediterranean shark problem
6.6 Answers to exercises
Chapter 7 Interpolation and fitting
7.1 Interpolation problem
7.2 Interpolation problem solved by MATLAB
7.3 Data fitting
7.4 Use MATLAB solves the curve fitting problem
7.5 Modeling case: Yellow River Xiaolangdi water and sediment regulation problem
7.6 Exercise
Chapter 8 Statistical description of data
8.1 Basic concepts of statistics
8.2 Parameter estimation
8.3 Hypothesis testing
8.4 Analysis of variance
8.5 MATLAB data statistics
8.6 Modeling case: Lathe Parts Failure Analysis
8.7 Exercises
Chapter 9 Statistical Analysis
9.1 Regression Analysis
9.2 Cluster Analysis
9.3 Discriminant Analysis
9.4 Principal Component Analysis
9.5 Time Series Analysis
9.6 Modeling Cases: Wine Evaluation
9.7 Exercises
Chapter 10 Fuzzy Comprehensive Evaluation
10.1 Weight Determination Method
10.2 Fuzzy Comprehensive Evaluation
10.3 Modeling Case: Evaluation of Yangtze River Water Quality
10.4 Exercises
Chapter 11 Computer Simulation
11.1 Monte Carlo Method
11.2 Generation of Simulated Random Numbers
11.3 Computer Simulation of Queuing Model
11.4 Solving Nonlinear Programming with Monte Carlo Method
11.5 Modeling Case: Optimal Design of
Car Light Source 11.6 Exercise
Chapter 12 Intelligent Algorithm
12.1 Genetic Algorithm
12.2 Simulated Annealing Algorithm
12.3 Ant Group Algorithm
12.4 Neural Network Method
12.5 Modeling Case: Traffic Patrol Service Platform Setting and Scheduling
12.6 Exercises