A four-way decision-making system for the Indian summer monsoon rainfall

Abstract

Due to non-stationary nature of Indian summer monsoon rainfall (ISMR), analysis of its patterns and behaviors is a very tedious task. Advance prediction and behaviors play a significant role in various domains. Literature review reveals that researchers’ works are limited to design predictive models but not on inherited patterns and behaviors for the ISMR. In this study, a novel method based on the hybridization of two computational techniques, viz., fuzzy and rough sets is proposed for patterns and behaviors. The proposed method initially classifies the information into the four distinct regions, as fuzzy positive region, fuzzy negative region, completely fuzzy region, and gray fuzzy region. Based on four regions, four different patterns of decision rules are explored. Further, a method is discussed to represent such decision rules in terms of graph, which helps to analyze the patterns of ISMR by discovering new knowledge. The proposed method is validated by performing various statistical analyses.