神經(jīng)網(wǎng)絡在高校圖書館圖書借閱流量預測中的應用
發(fā)布時間：2019-06-10 10:29
【摘要】：由于高校圖書館圖書借閱流量具有一定的非線性特性,傳統(tǒng)的回歸分析、灰色模型等方法難以處理這種非線性時間序列問題,影響了預測精度。為了提高預測精確度,提出粒子群優(yōu)化RBF神經(jīng)網(wǎng)絡的圖書借閱流量預測模型。該方法以圖書館圖書借閱流量歷史數(shù)據(jù)進行RBF神經(jīng)網(wǎng)絡建模,采用粒子群算法對RBF神經(jīng)網(wǎng)絡參數(shù)進行優(yōu)化,最后建立了圖書借閱流量動態(tài)響應模型。預測結果表明該模型預測結果合理,精度較高,為圖書館提高工作效率和服務質(zhì)量提供了參考依據(jù)。
[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.
【作者單位】： 廣西師范學院圖書館;
【分類號】：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.
【作者單位】： 廣西師范學院圖書館;
【分類號】：G250.7;G258.6;TP183
【相似文獻】
相關期刊論文 前10條
1 趙志剛;朱強;;圖書借閱管理系統(tǒng)的設計[J];浙江傳媒學院學報;2006年02期
2 宋明娥;;圖書借閱管理系統(tǒng)的設計與實施[J];新西部(下半月);2007年02期
3 白曉玲;;拓展高校圖書借閱網(wǎng)絡發(fā)展空間的探討[J];科技情報開發(fā)與經(jīng)濟;2008年35期
4 陳紅霞;;圖書館圖書借閱信息管理系統(tǒng)的應用分析[J];佳木斯教育學院學報;2013年01期
5 許珂;;關聯(lián)挖掘在圖書借閱數(shù)據(jù)庫中的應用[J];福建電腦;2006年09期
6 陳貴龍;計算機管理圖書借閱的功效[J];株洲工學院學報;1998年02期
7 張媛玲;;圖書借閱管理系統(tǒng)設計開發(fā)[J];科技致富向導;2014年21期
8 白彥峰,李林茹;基于Web的圖書借閱系統(tǒng)的設計和實現(xiàn)[J];現(xiàn)代圖書情報技術;2004年04期
9 李琦;利用OLE自動化增強圖書借閱系統(tǒng)報表功能[J];圖書情報工作;2003年11期
10 司貫中;劉e，
本文編號：2496394
本文鏈接：http://sikaile.net/tushudanganlunwen/2496394.html
