1. 1 linear programming problem

1.2 Income and risk of investment

Exercise 1

Chapter II Integer Programming

2. 1 Introduction

2.2 0- 1 integer programming

2.3 Monte Carlo method (random sampling method)

2.4 computer solution of assignment problem

Exercise 2

Chapter III Nonlinear Programming

3. 1 nonlinear programming model

3.2 Matlab solution of unconstrained problems

3.3 Constraint Extreme Value Problem

3.4 Flight management issues

Exercise 3

Chapter 4 Graph and Network Model and Method

4. Basic concept and data structure of1graph

4.2 Shortest Line Problem

4.3 Minimum Spanning Tree Problem

4.4 Network Maximum Flow Problem

4.5 Minimum Cost Maximum Flow Problem

4.6 Graph Theory Toolbox of MATLAB

4.7 Traveling Salesman (TSP) Problem

4.8 Plan review method and critical route method

4.9 ordering and transportation of steel pipes

Exercise 4

Chapter 5 interpolation and fitting

5. 1 interpolation method

5.2 Linear Least Squares Method for Curve Fitting

5.3 Least Square Optimization

5.4 Curve Fitting and Function Approximation

5.5 Yellow River Xiaolangdi water and sediment regulation

Exercise 5

Chapter 6 differential equation modeling

6. 1 why do you need a three-stage rocket to launch a satellite?

6.2 Population model

6.3 Matlab to find the symbolic solution of differential equation

6.4 Disposal of radioactive waste

6.5 numerical solution of MATLAB initial value problem

6.6 numerical solution of MATLAB boundary value problem

Exercise 6

Chapter VII Goal Planning

7. 1 Mathematical model of objective programming

7.2 Sequential algorithm for solving objective programming

7.3 Matlab solution of multi-objective programming

7.4 Example of Target Planning Model

7.5 data envelopment analysis

Exercise 7

Chapter VIII Time Series

8. 1 deterministic time series analysis method

8.2 stationary time series model

8.3 Matlab toolbox and commands related to time series

8.4 Arima sequence and seasonal sequence

Exercise 8

Chapter 9 Support Vector Machines

9. 1 Basic principle of support vector classifier

9.2 Matlab command of support vector machine and its application example

9.3 Diagnosis of Breast Cancer

Exercise 9

Chapter 10 multivariate analysis

10. 1 cluster analysis

10.2 principal component analysis

Factor analysis of 10.3

10.4 discriminant analysis

Canonical correlation analysis of 10.5

10.6 correspondence analysis

10.7 multidimensional scaling method

Exercise 10

Partial least squares regression analysis in chapter 1 1

Summary of 1 1. 1 partial least squares regression analysis

1 1.2 Matlab partial least squares regression command Plsregress

1 1.3 case analysis

Exercise 1 1

Chapter 12 modern optimization algorithm

12. 1 simulated annealing algorithm

12.2 genetic algorithm

12.3 improved genetic algorithm

12.4 Matlab genetic algorithm tool

Exercise 12

13 chapter digital image processing

13. 1 digital image overview

13.2 brightness transformation and spatial filtering

13.3 frequency domain transform

13.4 digital image watermark anti-counterfeiting

13.5 image encryption and hiding

Exercise 13

14 comprehensive evaluation and decision-making methods

14. 1 ideal solution

14.2 fuzzy comprehensive evaluation method

14.3 data envelopment analysis method

14.4 grey relational analysis method

14.5 principal component analysis method

14.6 rank sum ratio comprehensive evaluation method

14.7 case study

Exercise 14

Chapter 15 Forecast Method

15. 1 differential equation model

15.2 grey prediction model

15.3 regression analysis and prediction method

15.4 difference equation

15.5 Markov prediction

15.6 time series

15.7 interpolation and fitting

15.8 neural network

Exercise 15

Appendix a introduction of MATLAB software

A.1the use of MATLAB "help"

A.2 data entry

A.3 drawing command

A.4 the application of MATLAB in advanced mathematics

The application of A.5 Matlab in linear algebra

A.6 data processing

The use of appendix B Lingo software

B. Basic syntax of1lingo software

B.2 argot function

B.3 example of linear programming model

refer to