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Volume 2018, Article ID 1067927, 12 pages
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.


Due to the continuous progress in the field of vehicle hardware, the condition that a vehicle cannot load a complex algorithm no longer exists. At the same time, with the progress in the field of vehicle hardware, a number of studies have reported exponential growth in the actual operation. To solve the problem for a large number of data transmissions in an actual operation, wireless transmission is proposed for text information (including position information) on the basis of the principles of the maximum entropy probability and the neural network prediction model combined with the optimization of the Huffman encoding algorithm, from the exchange of data to the entire data extraction process. The test results showed that the text-type vehicle information based on a compressed algorithm to optimize the algorithm of data compression and transmission could effectively realize the data compression, achieve a higher compression rate and data transmission integrity, and after decompression guarantee no distortion. Therefore, it is important to improve the efficiency of vehicle information transmission, to ensure the integrity of information, to realize the vehicle monitoring and control, and to grasp the traffic situation in real time.