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Bike sharing demand prediction using artificial immune system and artificial neural network

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Abstract

From the viewpoint of bike sharing service, the rental number is a critical performance indicator for managers and controllers to assess the demand. Bike demand prediction in bike sharing systems is hence a key indicator in economic systems. In this study, a novel prediction framework integrating AIS and the artificial neural network forecasting technique is developed for numerical predication; it is named AIS-ANN. In this proposed AIS-ANN prediction framework, there are three major mechanisms applied to build the predication system which includes cell creation by ANN, antibody generation by clonal selection, and antibody’s center adaption by similarity measuring. The experimental results show that our proposed AIS-ANN has better performance when compared with other 6 forecasting models.

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Acknowledgements

This research is conducted under the support of Yuan Ze University. There are no other fundings for this research.

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Authors and Affiliations

  1. School of Software, Nanchang University, Nanchang, Jiangxi, China

    Pei-Chann Chang & Xiao-Yong Lu

  2. Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC

    Jheng-Long Wu

  3. College of Management and Economics, Tianjin University, Tianjin, China

    Yahui Xu & Min Zhang

  4. Office of Academic Affairs, Zhuhai College of Beijing Institute of Technology, Zhuhai, 519088, Guangdong, China

    Pei-Chann Chang

Authors
  1. Pei-Chann Chang
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  2. Jheng-Long Wu
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  3. Yahui Xu
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  4. Min Zhang
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  5. Xiao-Yong Lu
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Correspondence to Pei-Chann Chang.

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All authors of this research declare that they have no conflict of interest.

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Communicated by V. Loia.

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Chang, PC., Wu, JL., Xu, Y. et al. Bike sharing demand prediction using artificial immune system and artificial neural network. Soft Comput 23, 613–626 (2019). https://doi.org/10.1007/s00500-017-2909-8

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  • DOI: https://doi.org/10.1007/s00500-017-2909-8

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