Research on Librarian Demand Prediction Based on the GM (1,1) Model and BP Neural Network Combined Model

被引：0

作者：

Peng, Leilei ^{[1
]}

Liu, Ying ^{[1
]}

Chen, Ke ^{[1
]}

机构：

[1] Sichuan Univ, 24 South Sect 1,Yihuan Rd, Chengdu 610065, Peoples R China

来源：

ADVANCES IN WIRELESS COMMUNICATIONS AND APPLICATIONS, ICWCA 2021 | 2023年 / 299卷

关键词：

D O I：

10.1007/978-981-19-2255-8_12

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the development of science and technology, the automation level of library is constantly improving, and the number of librarians is decreasing year by year. As one of the most important human resources to promote the sustainable development of library, librarians are particularly important, therefore, it is necessary to research its changing trend. This study constructs a GM(1, 1)-BP Neural Network combined model, and takes the library of Sichuan University as case study. The simulation results show that, compared with a single prediction model, the GM (1, 1)-BP Neural Network combined model has higher prediction accuracy and smaller errors, which can further improve the prediction accuracy.

引用

下载

页码：115 / 124

页数：10

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