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

In order to solve the problem that the evaluation system of library electronic resource quality is not comprehensive and objective at present, we use RBF network to model the electronic resource quality evaluation system of university library. And compared with BP network modeling method and AHP. The experimental results show that the evaluation system model of university library’s electronic resources quality based on RBF neural network has more advantages than BP neural network model, and its results are more objective and comprehensive. This provides a new method and train of thought for the evaluation of electronic resources in university libraries.