1. Mathematical knowledge: This is the basis of mathematical modeling, including advanced mathematics, linear algebra, probability theory and mathematical statistics, and operational research. This knowledge can help us to understand and build mathematical models.
2. Computer programming: In practical application, we need to use computer programs to solve mathematical models. Therefore, it is very important to master one or more programming languages (such as MATLAB and Python).
3. Data analysis: Mathematical modeling often needs to deal with a large amount of data. Therefore, it is very useful to master the basic methods and tools of data analysis (such as Excel and SPSS).
4. Professional knowledge: According to the practical problems of modeling, you may need to master some relevant professional knowledge, such as physics, chemistry, biology, economy, management, etc.
5. Logical thinking ability: Mathematical modeling requires us to abstract complex practical problems into simple mathematical models, which requires strong logical thinking ability.
6. Innovative thinking ability: In the process of modeling, we need to constantly try new ideas and methods to find the best solution.
7. Teamwork: Mathematical modeling is usually a team work, so good teamwork is also very important.
Generally speaking, the basic knowledge of mathematical modeling covers mathematics, computer science, data analysis, professional knowledge, logical thinking, innovative thinking and teamwork.