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Shannon entropy maximization supplemented by neurocomputing to study the consequences of a severe weather phenomenon on some surface parameters
Published in Springer Netherlands
Volume: 93
Issue: 1
Pages: 237 - 247
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. © 2018, Springer Science+Business Media B.V., part of Springer Nature.
About the journal
JournalData powered by TypesetNatural Hazards
PublisherData powered by TypesetSpringer Netherlands
Open AccessNo