Comparative Analysis of Neutrosophic, Pythagorean neutrosophic, and Fermatean neutrosophic Soft Matrices in the context of Industrial Accidents: A Case Study

Abstract

Industrial accidents pose significant risks to human lives, the environment, and economic 
stability. This study presents a comparative analysis of three plithogenic frameworks—Neutrosophic 
soft sets, Pythagorean neutrosophic soft sets, and Fermatean neutrosophic soft sets—aiming to model 
and analyze industrial accidents. The primary objective is to evaluate the effectiveness of these soft 
sets in handling the uncertainties, complexities, and imprecisions inherent in accident data. Utilizing 
Dhar's (2021) algorithm for Neutrosophic soft matrices, we introduce a new parameter called a risk 
score, which consolidates various values for each industry or parameter into a singular magnitude. 
Our findings indicate that neutrosophic soft sets are more accurate than Pythagorean neutrosophic 
soft sets and Fermatean neutrosophic soft sets. The study concludes that adopting these advanced 
frameworks can enhance decision-making processes and safety protocols, thereby mitigating the 
adverse impacts of industrial accidents.