Prediction model of mobike demand based on T-GCN

Hongju Su; Jinbiao Nie; Yueying Li; Bei Zhuang; Shangjing Lin; Ji Ma; Jin Tian

doi:10.1117/12.2686589

10 August 2023 Prediction model of mobike demand based on T-GCN

Hongju Su, Jinbiao Nie, Yueying Li, Bei Zhuang, Shangjing Lin, Ji Ma, Jin Tian

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 1275931 (2023) https://doi.org/10.1117/12.2686589
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

Excessive delivery of shared bicycles will lead to a waste of resources. In order to improve the utilization of resources, it is necessary to forecast the demand for shared bicycles. Most of the previous papers only focus on demand data's temporal or spatial correlation. Our paper uses the T-GCN model, which takes into account not only temporal but also spatial correlations. Our research achieves better results on the problem of demand forecasting.

Citation Download Citation

Hongju Su, Jinbiao Nie, Yueying Li, Bei Zhuang, Shangjing Lin, Ji Ma, and Jin Tian "Prediction model of mobike demand based on T-GCN", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 1275931 (10 August 2023); https://doi.org/10.1117/12.2686589

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