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

Surajit Chattopadhyay (), Goutami Chattopadhyay and Subrata Kumar Midya
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Surajit Chattopadhyay: Amity University
Goutami Chattopadhyay: University of Calcutta
Subrata Kumar Midya: University of Calcutta

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 1, No 11, 237-247

Abstract: 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.

Keywords: Pre-monsoon thunderstorms; Probabilistic information theory; Shannon entropy; Entropy maximization (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3298-8

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