Probing the rainfall time series over northeast India through composite and binary fuzzy relation
Year: 2023
Type: article
Abstract: The current work reports a binary fuzzy relation (BFR) based approach to have an insight into the behavior of rainfall over northeast India. A fuzzy set is a generalization of classical sets, where the characteristic function is generalized to membership function to get hold of the scenarios that cannot be explained within the confinement of dichotomy. A fuzzy relation deals with the degree of belongingness of an ordered pair to some given relation and the most convenient way of representing it through a membership matrix. In this work we have considered Pre monsoon \({(X}_{1})\), Summer monsoon \({(X}_{2})\), Post monsoon \({(X}_{3})\) and Annual \({(X}_{4})\)rainfall for the period 1871–2016 over North-East India. We have considered BFR for the pairs (\({X}_{1}\),\({X}_{2}\)), \(\left({X}_{2},{X}_{3}\right),\left({X}_{3},{X}_{4}\right),\left({X}_{2},{X}_{4}\right)\). It may be noted that in this work we have considered the conditional probabilities of the bivariate frequency distributions as the membership grades for the corresponding BFR. In the next phase we have generated composition of 2 BFR’s through fuzzy max-min relationships. In this way we have compared the membership grades of the BFRs and the composite BFR’s to understand the roles played by summer monsoon rainfall and post monsoon rainfall in the annual rainfall and the study has concluded through the fuzzy cardinalities associated with the composite BFRs.
Authors: Rashmi Rekha Devi, Surajit Chattopadhyay
Institution: Amity University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4385876942