一种基于径向基网络的读者流失分析模型

大量而频繁的读者流失导致了图书馆知识服务范围的减少,降低了图书馆信息服务的质量。本文根据读者资料和借阅行为及其相关数据等历史信息,将径向基神经网络应用于读者流失分析中,针对目前图书借阅中存在的问题,给出了读者流失预测模型,利用训练后的模型对读者的流失率进行预测并生成读者列表。该模型通过试验运行,取得了良好的效果,对大学图书馆的服务策略实施具有现实的指导意义。

A Prediction Model of Reader Loss Analysis Based on RBF NN

Large and frequent loss of readers has led to the range reduction of library knowledge services,and reduced the quality of library information services.According to historical data of reader information and borrow behaviour,a certain RBF neural networks has been applied to reader loss analysis.For the problems existing in current reseach,a reader loss prediction model has been established.The loss probability of each reader has been computed by the model and possible loss reader list is recorded.The prediction model gets a satified results in the experimental test,which can be used to guide the service strategy of a university library.