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Travel Speed Prediction Using Fuzzy Reasoning

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Intelligent Robotics and Applications (ICIRA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5314))

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Abstract

The speed prediction algorithm introduced in this paper takes advantage of fuzzy systems that are insensitive to random noise, robust to uncertainties, and transparent to interpretation. The proposed algorithm for outlier detection selects the potential outliers based on the density rather than the deviation adopted in conventional approaches. To evaluate the developed system, a seris of experiments conducted on the real world data. The result of the comparison performed to evaluate the outliler detection method proposed reveals the benefit from the consideration of density. The cross validation results indicate the effectiveness of the fuzzy inference system developed.

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Author information

Authors and Affiliations

  1. Institute of Industrial Research, University of Portsmouth, Portsmouth, PO1 3QL, UK

    Yang Wang, Honghai Liu & David Brown

  2. Department of Mathematics, University of Portsmouth, Portsmouth, PO1 3HF, UK

    Patrick Beullens

Authors
  1. Yang Wang
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  2. Honghai Liu
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  3. Patrick Beullens
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  4. David Brown
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Editor information

Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China

    Caihua Xiong , Yongan Huang  & Youlun Xiong ,  & 

  2. Institute of Industrial Research, University of Portsmouth, Burnaby Building, PO1 3QL, Portsmouth, UK

    Honghai Liu

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© 2008 Springer-Verlag Berlin Heidelberg

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Wang, Y., Liu, H., Beullens, P., Brown, D. (2008). Travel Speed Prediction Using Fuzzy Reasoning. In: Xiong, C., Huang, Y., Xiong, Y., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2008. Lecture Notes in Computer Science(), vol 5314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88513-9_48

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  • DOI: https://doi.org/10.1007/978-3-540-88513-9_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88512-2

  • Online ISBN: 978-3-540-88513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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