Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66257
Title: A comparison study on electric vehicle growth forecasting based on grey system theory and NAR neural network
Authors: Zhang, X
Chan, KW
Yang, X
Zhou, Y
Ye, K
Wang, G
Keywords: EV charging demand forecasting
Grey system-forecasting theory
NAR neural network
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: 2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016, 2016, 7778845, p. 711-715 How to cite?
Abstract: Grey system forecasting theory model and nonlinear autoregressive (NAR) neural network model for forecasting the number of electric vehicles (EVs) in the city of Shenzhen are established in this paper separately. The number of EVs from 2006 to 2015 was used as the raw data in two models. The effectiveness of the two models are evaluated by various criteria. Afterward, the rationality, precision and the adaptability of the two models are compared. At last, the better model was used to forecasting the number of EVs in Shenzhen from 2016 to 2020.
Description: 7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016, Sydney, Australia, 6-9 November 2016
URI: http://hdl.handle.net/10397/66257
ISBN: 9781509040759
DOI: 10.1109/SmartGridComm.2016.7778845
Appears in Collections:Conference Paper

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