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Complexity
Volume 2018, Article ID 1067927, 12 pages
https://doi.org/10.1155/2018/1067927
Research Article

Vehicle Information Influence Degree Screening Method Based on GEP Optimized RBF Neural Network

1Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China
2Guangzhou Customs, Guangzhou 510623, China
3South China Agricultural University, Guangzhou 510642, China
4Guangzhou Xingwei Mdt InfoTech Ltd, Guangzhou 510630, China
5School of Computer Software in Tianjin University, Tianjin 300072, China
6North China Electric Power University, Beijing 102206, China
7College of Mechanical and Electrical Engineering, Foshan University, Foshan 528000, China

Correspondence should be addressed to Lufeng Luo; nc.ude.usof@gnefuloul

Received 23 March 2018; Revised 27 June 2018; Accepted 8 July 2018; Published 14 October 2018

Academic Editor: Andy Annamalai

Copyright © 2018 Jingfeng Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Jingfeng Yang, Nanfeng Zhang, Ming Li, et al., “Vehicle Information Influence Degree Screening Method Based on GEP Optimized RBF Neural Network,” Complexity, vol. 2018, Article ID 1067927, 12 pages, 2018. https://doi.org/10.1155/2018/1067927.