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Analyzing Accident Prone Regions by Clustering

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Advanced Topics in Intelligent Information and Database Systems (ACIIDS 2017)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 710))

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Abstract

Traffic accidents and injuries related to them have unfortunately become a daily incident for the people of Bangladesh and this is particularly true for people living in Dhaka City. This paper aims to identify the most hazardous regions for such incidents within the Dhaka Metropolitan Region as well as assess their influences. This research effort collects accident related data from the Accident Research Institute (ARI) at Bangladesh University of Engineering and Technology (BUET), Dhaka. This paper utilizes the k-means clustering and expectation maximization method to cluster related incidents together.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, North South University, Plot – 15, Block – B, Bashundhara, 1229, Dhaka, Bangladesh

    Shuvashish Paul, Ashik Mostafa Alvi, Mahmudul Alam Nirjhor, Shohanur Rahman, Adeeba Kashfee Orcho & Rashedur M. Rahman

Authors
  1. Shuvashish Paul
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  2. Ashik Mostafa Alvi
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  3. Mahmudul Alam Nirjhor
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  4. Shohanur Rahman
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  5. Adeeba Kashfee Orcho
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  6. Rashedur M. Rahman
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Corresponding author

Correspondence to Rashedur M. Rahman .

Editor information

Editors and Affiliations

  1. Faculty of Computer Sci. and Management, Wroclaw Univ. of Science and Technology Faculty of Computer Sci. and Management, Wroclaw, Poland

    Dariusz Król

  2. Faculty of Computer Sci. and Management, Wroclaw Univ of Science and Technology Faculty of Computer Sci. and Management, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. School of Advanced Sci. and Technology, Japan Advanced Inst. of Sci. and Tech School of Advanced Sci. and Technology, Ishikawa, Japan

    Kiyoaki Shirai

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Paul, S., Alvi, A.M., Nirjhor, M.A., Rahman, S., Orcho, A.K., Rahman, R.M. (2017). Analyzing Accident Prone Regions by Clustering. In: Król, D., Nguyen, N., Shirai, K. (eds) Advanced Topics in Intelligent Information and Database Systems. ACIIDS 2017. Studies in Computational Intelligence, vol 710. Springer, Cham. https://doi.org/10.1007/978-3-319-56660-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-56660-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56659-7

  • Online ISBN: 978-3-319-56660-3

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