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International Workshop on Agents and Data Mining Interaction

ADMI 2011: Agents and Data Mining Interaction pp 98–113Cite as

Agent-Based Cluster Analysis of Tropical Cyclone Tracks in the Western North Pacific

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7103))

Abstract

The clustering model integrating Finite Mixture Model (FMM) and classical Expectation-Maximum (EM) algorithm has been applied to tropical cyclone (TC) tracks during the last decade. However, the efficiency of classical EM algorithm is insufficiently good and the robustness of the model is not verified. Besides, it is inconvenient for users to manually choose the parameters for the cluster analysis. In order to improve the efficiency of classical EM algorithm, the “Lazy-Ψα2” EM is proposed by integrating Lazy EM algorithm and Ψα2 algorithm. Sensitivity analysis is conducted to ensure the insensitivity of the clustering model to the amount of data set. The cluster analysis is implemented on an agent-based framework by which the tool can automatically choose the parameters by evaluating the clustering performance. TC tracks in western North Pacific from 1949 to 2006 are classified into 12 clusters by the probabilistic clustering model that is solved by “Lazy-Ψα2” EM algorithm. The log-likelihood is taken as the performance indicator. Elaborate comparisons are made between the present cluster analysis and other cluster analyses related to TC tracks.

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Author information

Authors and Affiliations

  1. Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Wei Zhang

  2. Key lab of Geo-information Science, Ministry of Education, East China Normal University, Shanghai, China

    Yuanfei Wang

Authors
  1. Wei Zhang
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  2. Yuanfei Wang
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, PO Box 123, 2007, Sydney, NSW, Australia

    Longbing Cao

  2. Instituto de Informática, Universidade Federal do Rio Grande do Sul (UFRGS), Caixa Postal 15064, 91.501-970, Porto Alegre, RS, Brazil

    Ana L. C. Bazzan

  3. Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece

    Andreas L. Symeonidis

  4. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, 39, 14th Liniya, 199178, St. Petersburg, Russia

    Vladimir I. Gorodetsky

  5. Department of Knowledge Engineering, Maastricht University, P.O. Box 616, 6200, Maastricht, MD, The Netherlands

    Gerhard Weiss

  6. Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan Street, Room 1138 SEO, 60607, Chicago, IL, USA

    Philip S. Yu

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhang, W., Wang, Y. (2012). Agent-Based Cluster Analysis of Tropical Cyclone Tracks in the Western North Pacific. In: Cao, L., Bazzan, A.L.C., Symeonidis, A.L., Gorodetsky, V.I., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2011. Lecture Notes in Computer Science(), vol 7103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27609-5_8

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  • DOI: https://doi.org/10.1007/978-3-642-27609-5_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27608-8

  • Online ISBN: 978-3-642-27609-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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