System Development & Application
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2427-2431

Short-term demand prediction model for public bikes considering variable environmental factors

Qiao Jian
Chen Shaobo
He Mengying
School of Management, Northwestern Polytechnical University, Xi'an 710072, China
DOI: 10.19734/j.issn.1001-3695.2022.01.0024

Abstract

Existing short-term demand prediction models for public bikes ignore the difference in the nature of the impacts of different environmental factors on user demand as well as the temporal dependency of variable environmental factors. This paper distinguished environmental factors into the invariable factors that had been internalized into user demand and the variable factors that needed to be considered separately, and then proposed a model called GCNN-LSTM-E. In the model, it used graph convolutional neural network(GCNN) to capture the non-Euclidean spatial dependency of user demand, used long short-term memory(LSTM) network to capture the temporal dependencies of user demand and variable environmental factors, and applied vector concatenation and fully connected network to impose the influence of variable environmental factors on user demand. Experimental results show that the GCNN-LSTM-E model has the best prediction performance and outperforms all benchmark models under 1 h time granularity. It indicates that the design of the model is reasonable and effective, and 1 h is the most appropriate time granularity.

Foundation Support

国家自然科学基金资助项目(71971171)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.01.0024
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: System Development & Application
Pages: 2427-2431
Serial Number: 1001-3695(2022)08-031-2427-05

Publish History

[2022-03-25] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

乔健, 陈少博, 何梦莹. 考虑可变环境因素的公共自行车短期需求预测模型 [J]. 计算机应用研究, 2022, 39 (8): 2427-2431. (Qiao Jian, Chen Shaobo, He Mengying. Short-term demand prediction model for public bikes considering variable environmental factors [J]. Application Research of Computers, 2022, 39 (8): 2427-2431. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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