Abstract: How to evaluate the user satisfaction of college library objectively and accurately is always a difficult research topic. In recent years, BP neural network technology has become one of the hotspots in college library user satisfaction evaluation, which is fully based on objective data and exploits the potential useful information effectively and avoids the influence of subjective factors. Compared to the traditional BP neural network, RBF neural network can learn faster and converge more easily. This paper applied RBF neural network in the user satisfaction evaluation of college library, and expounded the design and implementation of evaluation model based on RBF neural network, and then analyzed the effectiveness of this model by example.

Key words: College library