Abstract

Study on the evaluation system of websites of college ideological and political education based on RBF neural network.

Author(s): Ran Ran, Meng Xin

Based on the characters and various index attributes of the websites of college ideological and political education, the multi-index hierarchical structure for evaluation on the competitiveness indexes of the websites of college ideological and political education was constructed by using expert grading method. The evaluation index system for competitiveness indexes of the websites of ideological and political education was built. Based on this, the competitiveness indexes of the websites of ideological and political education were measured and calculated to quantify the competitiveness level of the websites. Secondly, evaluation and study were carried out on the competitiveness indexes of the websites of ideological and political education by means of RBF neural network algorithm. The simulation results show that the method combining expert grading method and RBF neural network for measuring and calculating the competitiveness indexes of the websites of ideological and political education has high effectiveness and reliability.


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