In many cases, it is difficult to get the exact solution of the mathematical model established by practical problems, and it is usually necessary to find its approximate solution by numerical method. For example, the infinite calculation process is often replaced by a finite calculation process, and the error between the exact solution of this model and the approximate solution obtained by numerical method is called truncation error. Truncation error is inherent in numerical calculation method, also known as method error.

Truncation error, first of all, you need to know how the error comes from, and we will trace it back step by step. The error occurs because the predicted value is inconsistent with the real value. The predicted value is obtained by fitting. The fitting process is usually iterative, and the number of iterations may be many, even the fitting can not converge for a long time. You must set the maximum number of iterations or convergence accuracy.

Truncation error and rounding error are caused by calculation methods and are the main research objects of numerical calculation methods. When the mathematical model problem is transformed into a numerical problem, discretization and finite expansion are used, which leads to the error between the numerical problem and the mathematical model.

Numerical calculation methods used to solve mathematical models are often approximate methods, so only approximate solutions of mathematical models can be obtained. Because the approximation method generally replaces the infinite limit operation with a limited number of four arithmetic operation steps, the error caused by the truncation of the infinite process is the truncation error.