Application of Improved Clustering Algorithm in Financial Performance Evaluation of Colleges and Universities

Authors

  • Zhuyun Zhang, Yanjun Geng

Abstract

In this paper, the author researched on the application of improved clustering algorithm in financial performance evaluation of colleges and universities. This paper firstly defines the study object of the performance evaluation model, and selects sixty energy industry listed companies as the financial indicators data and then makes the normal distribution test on the financial indicators data and determines that they are suitable for factor analysis or not. Then, the logistic performance evaluation model is constructed based on the principal component factors screened by the forward stepwise variable selection method. Finally, this paper gets a good prediction of the model checking through the training and testing samples. The experiment result shows the financial performance can be improved by using improved clustering algorithm.

Published

2020-11-01

Issue

Section

Articles