Analysis of Performance Evaluation Model for Higher Education Informatization by Means of PLS-BP Model

Abstract

In order to improve the intelligent level of higher education informatization, a novel performance evaluation model of higher education informatization by means of PLS-BP model is proposed. The principles of partial least squares (PLS) method and back propagation (BP) neural network are introduced firstly. The main components of the data are extracted by PLS method, and then combined with BP neural network, the PLS-BP model is constructed. At the end of the article, the PLS-BP evaluation model is simulated and analyzed. From the comparison results, the error between the PLS-BP evaluation model and traditional performance evaluation is relatively small, and the maximum relative error is 2.32%. The comparison results verify the accuracy of the PLS-BP model. This model presented in this paper provides a new way for the performance evaluation of higher education informatization.