An Interpretation of the Surface Temperature Time Series through Fuzzy Measures

This paper reports a study to interpret the surface temperature based on time series and fuzzy measures. We demonstrated a method to identify the uncertainty around the surface temperature data concerning the summer monsoon in India. The random variables were standardized, and the Dempster-Shafer Th...

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Bibliographic Details
Published in:Axioms 2023-05, Vol.12 (5), p.475
Main Authors: Devi, Rashmi Rekha, Chattopadhyay, Surajit
Format: Article
Language:English
Subjects:
Atmospheric temperature
Climate change
Dempster-Shafer Theory
Fuzzy algorithms
Fuzzy logic
fuzzy set
Fuzzy systems
Identification methods
joint belief measure
northeast India
Polynomials
Probability
Random variables
Surface temperature
Temperature
Time series
Time-series analysis
Trends
Weather
Wind
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Summary:This paper reports a study to interpret the surface temperature based on time series and fuzzy measures. We demonstrated a method to identify the uncertainty around the surface temperature data concerning the summer monsoon in India. The random variables were standardized, and the Dempster-Shafer Theory was used to generate common goals. Two criteria, represented as fuzzy numbers, were used for this purpose. We constructed three polynomials to illustrate a functional connection between time series and the measure of joint belief. The analysis of the obtained results showed that the certainty increased over time. It confirmed that the degree of the evidence is a more predictable parameter at a more extended period.
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms12050475