神经网络在高校图书馆图书借阅流量预测中的应用
发布时间：2019-06-10 10:29
【摘要】：由于高校图书馆图书借阅流量具有一定的非线性特性,传统的回归分析、灰色模型等方法难以处理这种非线性时间序列问题,影响了预测精度。为了提高预测精确度,提出粒子群优化RBF神经网络的图书借阅流量预测模型。该方法以图书馆图书借阅流量历史数据进行RBF神经网络建模,采用粒子群算法对RBF神经网络参数进行优化,最后建立了图书借阅流量动态响应模型。预测结果表明该模型预测结果合理,精度较高,为图书馆提高工作效率和服务质量提供了参考依据。
[Abstract]:Because the book lending flow of university library has certain nonlinear characteristics, the traditional regression analysis, grey model and other methods are difficult to deal with this nonlinear time series problem, which affects the prediction accuracy. In order to improve the prediction accuracy, a book loan flow prediction model based on particle swarm optimization RBF neural network is proposed. In this method, the historical data of library book lending flow are used to model the RBF neural network, and the particle swarm optimization algorithm is used to optimize the parameters of RBF neural network. Finally, the dynamic response model of book lending flow is established. The prediction results show that the prediction results of the model are reasonable and the accuracy is high, which provides a reference for the library to improve the work efficiency and service quality.
【作者单位】： 广西师范学院图书馆;
【分类号】：G250.7;G258.6;TP183
[Abstract]:Because the book lending flow of university library has certain nonlinear characteristics, the traditional regression analysis, grey model and other methods are difficult to deal with this nonlinear time series problem, which affects the prediction accuracy. In order to improve the prediction accuracy, a book loan flow prediction model based on particle swarm optimization RBF neural network is proposed. In this method, the historical data of library book lending flow are used to model the RBF neural network, and the particle swarm optimization algorithm is used to optimize the parameters of RBF neural network. Finally, the dynamic response model of book lending flow is established. The prediction results show that the prediction results of the model are reasonable and the accuracy is high, which provides a reference for the library to improve the work efficiency and service quality.
【作者单位】： 广西师范学院图书馆;
【分类号】：G250.7;G258.6;TP183
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