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Shannon entropy maximization supplemented by neurocomputing to study the consequences of a severe weather phenomenon on some surface parameters

Author

Listed:
  • Surajit Chattopadhyay

    (Amity University)

  • Goutami Chattopadhyay

    (University of Calcutta)

  • Subrata Kumar Midya

    (University of Calcutta)

Abstract

An information theoretic approach based on Shannon entropy is adopted in this study to discern the influence of pre-monsoon thunderstorm on some surface parameters. A few parameters associated with pre-monsoon thunderstorms over a part of east and northeast India are considered. Maximization of Shannon entropy is employed to test the relative contributions of these parameters in creating this weather phenomenon. It follows as a consequence of this information theoretic approach that surface temperature is the most important parameter among those considered. Finally, artificial neural network in the form of multilayer perceptron with backpropagation learning is attempted to develop predictive model for surface temperature.

Suggested Citation

  • Surajit Chattopadhyay & Goutami Chattopadhyay & Subrata Kumar Midya, 2018. "Shannon entropy maximization supplemented by neurocomputing to study the consequences of a severe weather phenomenon on some surface parameters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 237-247, August.
    • Handle: RePEc:spr:nathaz:v:93:y:2018:i:1:d:10.1007_s11069-018-3298-8
    DOI: 10.1007/s11069-018-3298-8
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    References listed on IDEAS

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    1. Sutapa Chaudhuri, 2006. "Predictability Of Chaos Inherent In The Occurrence Of Severe Thunderstorms," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 9(01n02), pages 77-85.
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