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Research on vehicle intelligent wireless location algorithm based on convolutional neural network

  • S. I : Intelligent Computing Methodologies in Machine learning for IoT Applications
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Abstract

Vehicle positioning and vehicle identification of natural scene images are an important part of intelligent transportation systems and unmanned driving research. In current situation, there are still some problems in vehicle intelligent wireless positioning. In order to improve the intelligent wireless positioning efficiency of vehicles, based on the convolutional neural network, this research combines the concept of deep learning to carry out algorithm innovation in the research. Moreover, this paper combines the actual vehicle positioning problem points to collect data, simulates the vehicle positioning situation in a variety of complex situations, and designs a controlled test to verify. The results show that the algorithm of this study has certain effects, which can provide reference for subsequent related research and has certain practical significance.

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Acknowledgement

This study was supported by National Natural Science Foundation of China (No. 31702232), Education teaching reform project of Henan (No. 2019-JSJYYB-056) and Education teaching reform project of Zhoukou normal university (No. J2019002).

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Authors and Affiliations

  1. School of Mathematics and Statistics, ZhouKou Normal University, 466001, Zhoukou, Henan, China

    Yazi Wang

  2. College of Applied Sciences, Beijing University of Technology, 100022, Beijing, China

    Yuehong Feng

  3. School of Mathematics and Statistics, Fuyang Normal University, 466001, Fuyang, Henan, China

    Huaibo Sun

Authors
  1. Yazi Wang
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  2. Yuehong Feng
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  3. Huaibo Sun
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Correspondence to Huaibo Sun.

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Wang, Y., Feng, Y. & Sun, H. Research on vehicle intelligent wireless location algorithm based on convolutional neural network. Neural Comput & Applic 33, 8131–8141 (2021). https://doi.org/10.1007/s00521-020-04911-w

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  • DOI: https://doi.org/10.1007/s00521-020-04911-w

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