Research on the Prediction Method for Library Reader Flow Based on Evolutionary Neural Network

Abstract:

It is an important work for modern libraries to predict reader flow. With the help of reader flow, library staff can grasp the change regulation of readers, allocate tasks rationally and take steps ahead of time in high-risk period. Because of reader flows typical non-linear characteristics, evolutionary neural network technology is introduced in this research so as to improve the accuracy of reader flow prediction. A prediction method for library reader flow based on evolutionary neural network is proposed. Genetic algorithm is used to optimize and design BP neural network firstly, then evolutionary neural network is used to predict reader flow. The experimental results show that evolutionary neural network is an effective tool for us to predict library reader flow. We can realize an accurate prediction for library reader flow by this method.

• Periodical: Applied Mechanics and Materials (Volumes 543-547)
• Pages: 2128-2132
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.543-547.2128
• Online since: March 2014
• Authors: Ping Wang*
• Keywords: BP Algorithm, Evolutionary Neural Network, Library, Reader Flow Prediction

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DOI: 10.1109/cecnet.2012.6202141