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Traffic Flow Prediction with Improved SOPIO-SVR Algorithm

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Challenges and Opportunity with Big Data (Monterey Workshop 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10228))

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Abstract

In urban public transport, the traffic flow prediction is a classical non-linear complicated optimization problem, which is very important for public transport system. With the rapid development of the big data, Smart card data of bus which is provided by millions of passengers traveling by bus across several days plays a more and more important role in our daily life. The issue that we address is whether the data mining algorithm and the intelligent optimization algorithm can be applied to forecast the traffic flow from big data of bus. In this paper, a novel algorithm which called mixed support vector regression with sub-space orthogonal pigeon-Inspired Optimization (SOPIO-MSVR) is used to predict the traffic flow and optimize the algorithm progress. Results show the SOPIO-MSVR algorithm outperforms other algorithms by a margin and is a competitive algorithm. And the research can make the significant contribution to the improvement of the transportation.

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Acknowledgments

The research is supported by the NSFC (National Science Foundation of China) Projects (No. 61572057) in China, the National High-Tech Research and Development Plan of China under Grant No. 2015AA042101.

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China

    Xuejun Cheng, Lei Ren, Jin Cui & Zhiqiang Zhang

  2. Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, China

    Xuejun Cheng, Lei Ren, Jin Cui & Zhiqiang Zhang

Authors
  1. Xuejun Cheng
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  2. Lei Ren
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  3. Jin Cui
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  4. Zhiqiang Zhang
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Corresponding author

Correspondence to Lei Ren .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Lin Zhang

  2. Beihang University, Beijing, China

    Lei Ren

  3. Université Pierre and Marie Curie, Paris, France

    Fabrice Kordon

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Cheng, X., Ren, L., Cui, J., Zhang, Z. (2017). Traffic Flow Prediction with Improved SOPIO-SVR Algorithm. In: Zhang, L., Ren, L., Kordon, F. (eds) Challenges and Opportunity with Big Data. Monterey Workshop 2016. Lecture Notes in Computer Science(), vol 10228. Springer, Cham. https://doi.org/10.1007/978-3-319-61994-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-61994-1_17

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  • Online ISBN: 978-3-319-61994-1

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