1. linear algebra: linear algebra is the basis of mathematical modeling, including matrix operation, vector space, eigenvalues and eigenvectors. This knowledge is very useful in solving optimization problems, data analysis and other problems.
2. Calculus: Calculus is a branch of mathematics that studies the rate of change and accumulation, including limit, derivative and integral. This knowledge is very important for building models and solving equations.
3. Probability theory and mathematical statistics: Probability theory and mathematical statistics are branches of mathematics that study random phenomena, including probability distribution, hypothesis testing and regression analysis. This knowledge is very useful for dealing with uncertainty and predicting the future.
4. Optimization theory: Optimization theory is a branch of mathematics that studies how to find the optimal solution, including linear programming, nonlinear programming and integer programming. This knowledge is very important for solving problems such as resource allocation and path planning.
5. Graph theory: Graph theory is a branch of mathematics that studies graph structure, including graph representation, traversal and shortest path. This knowledge is very useful in solving problems such as network traffic and social networks.
6. Numerical analysis: Numerical analysis is a branch of studying how to solve mathematical problems approximately by numerical methods, including interpolation, approximation and numerical solutions. This knowledge is very useful when dealing with large-scale data and complex calculations.
7. Discrete mathematics: Discrete mathematics is a branch of mathematics that studies discrete objects, including set theory, logic and combinatorial mathematics. This knowledge is very useful in solving coding and cryptography problems.
8. Function theory: Function theory is a branch of mathematics that studies the properties of functions, including real analysis and complex analysis. This knowledge is very useful in dealing with complex functional relations, signal processing and other issues.
These are just some basic math knowledge. In fact, the topic of the mathematical modeling contest may involve more mathematical fields. So you need to have extensive mathematical knowledge and the ability to use it flexibly. At the same time, you need to master some programming skills, such as Python and MATLAB, in order to realize your model and algorithm.