Vector algebra, vector analysis, tensor analysis

Matrix algebra, matrix analysis

Analytic geometry

Functional analysis, variational method

ordinary differential equation

optimization method

Graphics and network model

Stochastic mathematics (probability, statistics, stochastic process)

Computational intelligence (artificial neural network, genetic algorithm, SVM, etc.). ) model

Pattern recognition, machine learning, data mining

How to solve the mathematical model

Computational linear algebra, linear programming, numerical analysis

Numerical solutions of nonlinear problems (nonlinear equations, nonlinear function minimization, nonlinear least square method)

function of a complex variable

Boundary value problem of differential equation

Combinatorial optimization, graph theory algorithm

computing geometry

The key to learning lies in practice and in integrating the ideas of geometry, analysis and algebra. One-sided pursuit of knowledge will not be very effective in practical work. On the contrary, if we put some key ideas into it, we can get the effect of analogy.

Calculation/modeling/simulation tools

matlab

mathematics

maple

online library

NEOS)