基于SSA-BPNN的图书馆服务用户满意度评价研究

Study on Library Service user satisfaction evaluation based on SSA-BPNN

为了改善读者对读者满意程度的评估,BP神经网络在求解过程中会出现局部优化和缓慢的问题,基于BP网络的“麻雀”的检索方法对图书馆服务顾客满意程度进行评估。首先,运用层次分析法从用户期望、感知价值、图书馆形象、用户忠诚、服务满意度和用户抱怨等6个方面构建出用户满意度评价指标体系;其次,运用麻雀搜索算法优化BP神经网络进行图书馆服务用户满意度评价。与FA-BPNN、PSO-BPNN、GA-BPNN和BPNN相比较,SSA-BPNN模型的读者对图书馆的满意程度为最佳评估,为读者的满意程度提供一种新的途径。

In order to improve the evaluation of patron satisfaction,BP neural network in the process of solving the problem of local optimization and slow,based on the BP network"sparrow"search method to assess the satisfaction of library service customers.Firstly,a user satisfaction evaluation index system is constructed using hierarchical analysis from six aspects,including user expectations,perceived value,library image,user loyalty,service satisfaction and user complaints;secondly,a sparrow search algorithm is used to optimize the BP neural network for library service user satisfaction evaluation.Compared with FA-BPNN,PSO-BPNN,GA-BPNN and BPNN,the SSA-BPNN model has the best assessment of patrons'satisfaction with the library,providing a new way for the satisfaction level of patrons.