An information-theoretic study of rainfall time series through the Dempster–Shafer approach over a meteorological subdivision of India. Issue 6 (21st October 2022)

• Record Type: Journal Article
• Authors: Devi, Rashmi Rekha; Chattopadhyay, Surajit
• Is Part Of: Journal of hydroinformatics. Volume 24:Issue 6(2022)
• Page Start: 1269
• Page End: 1280
• Publication Date: 2022-10-21
• Subjects: Dempster–Shafer theory -- fuzzy set -- joint belief measure -- northeast India -- rainfall; Hydrology -- Data processing -- Periodicals; Geographic information systems -- Periodicals; Geographic information systems; Hydrology -- Data processing; Electronic journals; Periodicals; 551.480285
• DOI: 10.2166/hydro.2022.192
• Languages: English
• ISSNs: 1464-7141

Abstract

Abstract: The present paper reports a study, where we have developed a methodology to understand the relative uncertainty associated with the rainfall amount corresponding to summer monsoon (JJAS) and post monsoon (OND) for the period 1871–2016 over northeast India. After calculating the partial correlation between two random variables after the removal of the effect of the third one, we have standardized all the realizations of the random variables. Subsequently, after applying the Dempster–Shafer theory, we have obtained joint basic assignments through two judging criteria for the fuzzy sets representing the closeness of the observed values to two measures of central tendency for different window sizes obtained from the original time series. The study revealed a higher rate of increase in the uncertainty with a change in the window size for OND than in the case of JJAS. This study finally concluded that this approach could generate some idea about the most advantageous ratio of training and test cases for predictive models with supervised learning procedures. HIGHLIGHTS: Using the Dempster–Shafer theory, we are able to determine joint basic assignments for fuzzy sets. For OND, the study found a larger increasing pattern in uncertainty with a change in the window size than for JJAS. We have seen that for OND, the surface lifts significantly as the leading coefficient of the polynomial changes. But, in the case of JJAS, no such significant effect is being noticed.