Also known as computer random simulation method, also known as statistical experiment method. You can test the correctness of your model by simulation.

2. Data processing, such as data fitting, parameter estimation and interpolation.

There are a lot of data to be processed in the competition, and the key to data processing lies in these methods, which are usually assisted by matlab and can also deal with many fitting problems in combination with graphics.

3. Programming problem algorithm:

Including linear programming, integer programming, multivariate programming, quadratic programming, etc. Many problems in the competition are related to planning. It can be said that many models can be reduced to a set of inequalities as constraints and several function expressions as objective functions. Solving such a problem is the key.

This kind of problem can generally be solved by lingo software.

4. Graph theory problems:

This paper mainly studies the algorithms of this kind of problems, including Dijkstra, Floyd, prime number, Bellman-Ford, maximum flow, binary matching and so on. It shouldn't be difficult for people familiar with ACM.

5. Problems in computer algorithm design;

The algorithm design includes: dynamic programming, backtracking search, divide and conquer, branch and bound method (solving integer solutions) and so on.

6. Three non-classical algorithms of optimization theory:

A) simulated annealing

B) neural network

genetic algorithm

7. Grid algorithm and exhaustive algorithm

8. Discretization method for continuous problems

Because computers can only deal with discrete problems, and most of the data in reality are continuous, it is necessary to discretize the continuous problems before solving them with computers.

For example, the idea of difference instead of differential and summation instead of integral are all common methods to discretize continuous problems.

9. Numerical analysis method

This paper mainly studies various numerical calculation methods for solving mathematical problems, especially the methods and algorithms suitable for computer implementation.

Including: numerical approximation of functions, numerical differentiation and numerical integration, numerical solutions of nonlinear regression, numerical algebra, numerical solutions of ordinary differential equations, etc.

Matlab is mainly used to solve this problem.

10. Image processing algorithm

This part mainly uses matlab for image processing.

Including showing pictures, explaining questions and so on.