基于神经网络的读者满意度评价方法研究

Research on Reader Satisfaction Evaluation Method Based on Neural Network

通过运用神经网络的原理及应用优势,分析了影响图书馆读者满意度的因素,提出了基于径向基函数神经网络(RBF网络)的读者满意度评价指标体系,建立了以蚌埠学院图书馆为例的读者满意度高的智能化评价模型,最后结合SPSS重要性分析对影响因素进行梳理,充分利用神经网络在图书馆读者满意度测评中的精准判断和预测,进而对图书馆未来的优化管理提出合理性建议。

By using the principle and application advantages of neural network,analyzes the factors affecting reader satisfaction in library,puts forward an evaluation index system of reader satisfaction based on radial basis function neural network(RBF network),and establishes an intelligent evaluation model with high reader satisfaction taking Bengbu University Library as an example.Finally,the paper sorts out the influencing factors by combining the importance analysis of SPSS,makes full use of the accurate judgment and prediction of the satisfaction of library readers,and then puts forward reasonable suggestions for the future optimization management of the library.