Research on the Quality Evaluation System of University Library Electronic Resources Based on RBF Neural Network

EasyChair Preprint 1298, version 1

Abstract

In order to solve the problem that the evaluation of library electronic resources quality evaluation system is not comprehensive and objective, we use RBF network to model the electronic resource quality evaluation system of efficient library and model with BP network.The experimental results show that the RBF neural network based on the university library electronic resources quality evaluation system model has greater advantages than the BP neural network model, and the results are more objective and comprehensive, which provides a new method and idea for the university library electronic resources quality evaluation.In order to solve the problem that the evaluation of library electronic resources quality evaluation system is not comprehensive and objective, we use RBF network to model the electronic resource quality evaluation system of efficient library and model with BP network.The experimental results show that the RBF neural network based on the university library electronic resources quality evaluation system model has greater advantages than the BP neural network model, and the results are more objective and comprehensive, which provides a new method and idea for the university library electronic resources quality evaluation.

Keyphrases: BP neural network, Quality evaluation system, RBF neural network, library electronic resources

@booklet{EasyChair:1298,
  author    = {Dongzhe Wang and Haiyan Xie and Gaohu Meng and Zhiqi Liu},
  title     = {Research on the Quality Evaluation System of University Library Electronic Resources Based on RBF Neural Network},
  howpublished = {EasyChair Preprint 1298},
  year      = {EasyChair, 2019}}