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Fuzzy APPSS: A novel method for quantifying COVID-19 impact in India under triangular spherical fuzzy environment
Aicevarya Devi Sakthivel1, Felix Augustin2
1Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, 600127, Chennai, India.
Scientific Reports
|December 27, 2024
Summary
A new fuzzy decision-making method, APPSS, using triangular spherical fuzzy numbers (TSFN) identifies COVID-19
Area of Science:
- Decision Sciences
- Fuzzy Mathematics
- Public Health
Background:
- Decision-making models are crucial for real-world problem analysis.
- Fuzzy decision-making models address dynamic problem complexities.
- Advanced techniques are needed for real-time uncertainty assessment.
Purpose of the Study:
- Introduce the Association between Preference and Performance with Satisfactory Score (APPSS) method.
- Develop a novel fuzzy decision-making approach using triangular spherical fuzzy numbers (TSFN).
- Analyze the impact of COVID-19 on different age groups in India.
Main Methods:
- Developed the APPSS method integrating preference and performance components.
- Utilized triangular spherical fuzzy numbers (TSFN) for enhanced uncertainty handling.
- Applied a new scoring function for TSFN based on the graded mean integration method.
Main Results:
- The APPSS method effectively analyzes complex decision-making scenarios.
- Identified the 60-69 age group as highly vulnerable to COVID-19 in India.
- Sensitivity and comparative analyses confirmed the robustness of the findings.
Conclusions:
- The APPSS method provides a reliable framework for fuzzy decision-making.
- Findings offer insights into COVID-19's differential impact across age groups.
- Results support policymakers in assessing future health risks and complications.
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