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Enhancing Cholera Outbreaks Prediction Performance in Hanoi, Vietnam Using Solar Terms and Resampling Data

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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10448))

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Abstract

A solar term is an ancient Chinese concept to indicate a point of season change in lunisolar calendars. Solar terms are currently in use in China and nearby countries including Vietnam. In this paper we propose a new solution to increase performance of cholera outbreaks prediction in Hanoi, Vietnam. The new solution is a combination of solar terms, training data resampling and classification methods. Experimental results show that using solar terms in combination with ROSE resampling and random forests method delivers high area under the Receiver Operating Characteristic curve (AUC), balanced sensitivity and specificity. Without interaction effects the solar terms help increasing mean of AUC by 12.66%. The most important predictor in the solution is Sun’s ecliptical longitude corresponding to solar terms. Among the solar terms, frost descent and start of summer are the most important.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, VNUH University of Engineering and Technology, Hanoi, Vietnam

    Nguyen Hai Chau

Authors
  1. Nguyen Hai Chau
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Correspondence to Nguyen Hai Chau .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management , Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of MĂĽnster, MĂĽnster, Germany

    Gottfried Vossen

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Chau, N.H. (2017). Enhancing Cholera Outbreaks Prediction Performance in Hanoi, Vietnam Using Solar Terms and Resampling Data. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-67074-4_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67073-7

  • Online ISBN: 978-3-319-67074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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