For example, Dijkstra or Floyd algorithm is used in graph theory, and genetic algorithm and grey prediction are used in statistics. Similar to the theoretical basis of these methods, it can be simply explained in model preparation because it is inconvenient to establish and solve the expansion model.

The role of this part of the model preparation is to make the paper clear and play a role from the shallow to the deep. Similar to model hypothesis and symbolic interpretation, it plays a paving role in this paper.

Thinking method:

Mathematical modeling is a mathematical thinking method, and it is a powerful mathematical means to describe and "solve" practical problems by using mathematical language and methods through abstraction and simplification.

Mathematical modeling is a process of describing actual phenomena with mathematical language. The actual phenomena here include both concrete natural phenomena, such as free fall, and abstract phenomena, such as customers' value tendency to a certain commodity. The description here includes not only the description of external form and internal mechanism, but also the prediction, experiment and explanation of actual phenomena.

We can also intuitively understand this concept: mathematical modeling is a process that makes pure mathematicians (mathematicians who only study mathematics and don't care about its application in practice) become physicists, biologists, economists and even psychologists.

Refer to the above content: Baidu Encyclopedia-Mathematical Modeling