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Soft Computing

, Volume 23, Issue 2, pp 613–626 | Cite as

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

  • Pei-Chann ChangEmail author
  • Jheng-Long Wu
  • Yahui Xu
  • Min Zhang
  • Xiao-Yong Lu
Methodologies and Application

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.

Keywords

Bio-inspired computation Artificial immune system Artificial neural network Numerical prediction Bike sharing demand 

Notes

Acknowledgements

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

Compliance with ethical standards

Conflict of interest

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

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.School of SoftwareNanchang UniversityNanchangChina
  2. 2.Institute of Information ScienceAcademia SinicaTaipeiTaiwan, ROC
  3. 3.College of Management and EconomicsTianjin UniversityTianjinChina
  4. 4.Office of Academic AffairsZhuhai College of Beijing Institute of TechnologyZhuhaiChina

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