An Analytical Estimation on The Factors Affected Students’ Education After COVID-19 Pandemic Via Dempster-Shafer Theory of Evidence

Abstract

Introduction: Dempster-Shafer Theory (simply D-S Theory) is developed by Arthur P. Dempster and Glenn Shafer. This theory is widely used in many fields. One advantageous aspect of this is the ability to incorporate additional data into D-S Theory. However, it is important to note that the computational process necessitates a significant amount of effort due to the complexities involved with  of sets.

Objectives: This study focuses on combination rule for multiple basic probability assignments in uncertain environment.

Methods: An algorithm has been developed and a python program has also been generated to validate combination rule for multiple basic probability assignments. Tableau software is utilized for illustrating data visualization.

Results: This concept has been implemented by the factors contributing to the decline in students’ studies after the COVID-19 pandemic by the way of adopting fuzzy numbers.

Conclusions: Final output is tabulated which are obtained by generated python program. That clearly shows the highest impact factor affected students’ studies after COVID-19 pandemic. In future, it is decided to study more number of real-life applications based on fuzzy evidence theory in our Research.