Introduction to Mathematical Modeling

Mathematical modeling is divided into three large pieces:

Modeling, programming, writing papers

Mathematical modeling has ten models:

① assessment class model

AHP

TOPSIS method (de-merits of distance method)

② interpolation and fitting models

Polynomial interpolation, Hermite interpolation segment interpolation, spline interpolation (one-dimensional), n-dimensional interpolation data (learn)

cftool Toolbox

③ correlation model

The correlation coefficient: Pearson and Spearman person spearman (accompanying explanation: data descriptive statistics)

Canonical Correlation Analysis

④ regression model

Multiple regression analysis

Stepwise regression analysis

Lasso regression and ridge regression

⑤ graph theory

Dijstra Dijkstra

Floyd algorithm

⑥ classification

Binary: Logistic Regression, Fisher category analysis, SVM support vector machine

Multi-Category: Multiple Logistic Regression Model

⑦ cluster model

K-Mean algorithm and K-Means ++ algorithm

DBSCAN clustering algorithm

⑧ Time Series Models

AR, MA, ARMA model

ARCH and GARCH

Time series unit root

⑨ prediction model

Interpolation prediction model

Time Series Prediction

Gray Forecasting Model

BP neural network

⑩ dimension reduction model

SVD Singular Value Decomposition (mainly for image processing)

Principal component analysis

factor analysis

Guess you like

Origin www.cnblogs.com/wisir/p/11541518.html