基于径向基神经网络的数字馆藏质量评价研究

Evaluation and Study of the Quality of Digital Collections Based on RBF Neural Network

根据径向基神经网络的自组织、自学习和自适应等特性,提出了基于径向基神经网络的数字馆藏质量评价方法,建立了评价模型,运用该模型对山东省烟台和威海地区的5所高校图书馆的数字馆藏进行了质量评价。通过MATLAB仿真试验结果分析,证明了其可行性和有效性。

According to the self-organizing, self-learning and self-adapting characteristics of RBF neural network, this paper describes a method for evaluating the quality of digital collections based on RBF neural network, and constructs an evaluation model. The model is used to evaluate the quality of digital collections of 5 university li- braries in Yantai and Weihai regions, Shandong Province. Analysis of the resuh of MATLAB simulation test proves that the model is feasible and effective.