What are the common mathematical models?

Mathematical models are tools to abstract and describe phenomena, processes or problems in the real world. They are usually used to predict, explain and analyze various phenomena. The following are some common mathematical models:

1. Linear regression model: This is one of the simplest statistical models used to describe the relationship between two or more variables. It assumes that there is a linear relationship between output variables and input variables.

2. logistic regression model: this is a classification model used to predict whether an event will happen. It is based on the probability of an event, not certainty.

3. Time series model: This model is used to analyze and predict time-varying data. For example, stock prices, weather patterns, etc.

4. Markov chain model: This is a stochastic process model used to describe the transition probability of the system between different states.

5. Bayesian network model: This is a graphical model used to represent the conditional probability relationship between variables.

6. Used to deal with complex nonlinear problems.

7. Support vector machine model: This is a supervised learning model used for classification and regression analysis.

8. Decision tree model: This is a tree structure model used to represent the decision-making process.

9. Monte Carlo simulation model: This is a method to estimate numerical results by repeated random sampling.

1. Optimization model: This is a problem-solving method to find the optimal solution, such as linear programming and integer programming.