Title
Bike sharing demand prediction using artificial immune system and artificial neural network.
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.
Year
DOI
Venue
2019
10.1007/s00500-017-2909-8
Soft Comput.
Keywords
Field
DocType
Bio-inspired computation, Artificial immune system, Artificial neural network, Numerical prediction, Bike sharing demand
Artificial immune system,Performance indicator,Computer science,Artificial intelligence,Artificial neural network,Clonal selection,Machine learning
Journal
Volume
Issue
ISSN
23
2
1432-7643
Citations 
PageRank 
References 
0
0.34
26
Authors
5
Name
Order
Citations
PageRank
Pei-Chann Chang11752109.32
Jheng-Long Wu2959.54
Yahui Xu300.34
Min Zhang430.72
Xiao-Yong Lu500.68