How to take a mathematical problem from practical to abstract

Abstract thinking is the process in which people use concepts, judgments, reasoning and other forms of thinking to indirectly and generalize the objective reality in cognitive activities. To put it simply, abstraction is generalization, learning to analyze concrete things and generalize the general regularities in them. In order to elevate mathematical problems from practical to abstract, they must be decontextualized and not confined to the individual attributes of concrete things.

The written language is mathematical, and the mathematical problems are generalized.

Summary. In order to solve this problem, through problem abstraction and mathematical modeling, it can be transformed into a mathematical model, that is, to solve an optimization problem, so that the optimal solution can be solved under certain constraints. The methods and practices to solve this problem are as follows:

1.First, the goal of the problem should be clarified, that is, the optimal solution of the required solution, as well as the constraints. 2.Then, according to the objectives and constraints of the problem, a mathematical model is constructed, that is, an optimization problem is solved. 3.

Then, according to the constructed mathematical model, the optimal solution was solved by using mathematical optimization methods. 4.Finally, according to the optimal solution, the final conclusion is drawn. When solving this problem, it is necessary to master some mathematical optimization methods, such as gradient descent method, Newton method, quasi-Newtonian method, etc., as well as some basic knowledge of mathematical modeling, such as linear programming, nonlinear programming, quadratic programming, etc.

In order to solve this problem, through problem abstraction and mathematical modeling, it can be transformed into a mathematical model, that is, to solve an optimization problem, so that the optimal solution can be solved under certain constraints. The methods and practical steps to solve this problem are as follows:1

First, the goal of the problem should be clarified, that is, the optimal solution of the required solution, as well as the constraints. 2.Then, according to the objectives and constraints of the problem, a mathematical model is constructed, that is, an optimization problem is solved. 3.Then, according to the constructed mathematical model, the optimal solution was solved by using mathematical optimization methods. 4.

Finally, according to the optimal solution, the final conclusion is drawn. When solving this problem, it is necessary to master some mathematical optimization methods, such as gradient descent method, Newton method, quasi-Newtonian method, etc., as well as some basic knowledge of mathematical modeling, such as linear programming, nonlinear programming, quadratic programming, etc.

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For this problem, through problem abstraction and mathematical modeling, it can be transformed into a concrete mathematical model for more in-depth analysis and solution. Mathematical modeling is the process of turning a practical problem into a mathematical model, which can help us understand the problem better and can provide more information in order to better solve the problem. The process of mathematical modeling includes problem abstraction, mathematical modeling, mathematical analysis, and solution solving.

First, the problem needs to be abstracted and the actual problem is transformed into a mathematical model for deeper analysis and solution. Secondly, to do mathematical modeling, to build a mathematical model so that the problem is better understood, and more information can be provided in order to better solve the problem. Finally, there is a mathematical analysis, the mathematical model is analyzed so that the problem is better understood, and more information can be provided so that the problem can be solved better.

Mathematical modeling is an effective way to solve practical problems, it can help us understand the problem better, and it can provide more information in order to solve the problem better. It helps us understand the problem better and can provide more information so that we can solve the problem better. In addition, mathematical modeling can also help us analyze problems better and thus solve them better.