A Novel Method of Support Vector Machine for the Evaluation and Optimization of Financial Management

Abstract

Evaluation optimization is the major content of financial management, but in the evaluation and optimization process, the number of financial data and evaluation means will affect the outputs, decrease the accuracy of evaluation optimization, and lead to errors in optimization results. Rest on this, this paper develops a support vector machine technique to evaluate and optimize financial management, maximize the level of financial management, and shrink the evaluation and optimization time. Then, a comprehensive assessment of financial management is carried out. Finally, vector computing manages evaluation optimization and outputs the optimization outputs. The simulation outputs of MATLAB represent that the support vector machine method can accurately evaluate and optimize, improve the level of financial management, and the evaluation and optimization accuracy is more significant than 92%, which is better than the vector calculation method. At the same time, the results of the support vector machine technique developed in this paper have a small change range, less than 3.6%, which is superior to the original calculation method. In addition, in the financial management, support vector machine method for data processing time is less than 5 seconds, better than manual evaluation method. Therefore, the support vector machine method can meet the evaluation necessity of financial management and is perfect for optimal financial management analysis.