Safety Management Dataset

This repository contains the Safety Management Dataset, developed to support research in advanced fuzzy decision-making, industrial safety management, and hazard risk assessment under uncertain and complex operational environments. The dataset is intended for evaluating safety response strategies using multi-criteria decision-making (MCDM) techniques based on advanced fuzzy set theories. The dataset consists of multiple safety management alternatives assessed across various decision criteria, including hazard severity, operational reliability, response effectiveness, worker safety, environmental impact, resource allocation, system resilience, and mitigation efficiency. Each evaluation is represented using Circular Complex Fermatean Fuzzy Information, enabling the effective modeling of uncertainty, ambiguity, hesitation, and complex-valued information encountered in real-world industrial safety applications. The dataset was developed to validate an advanced Circular Complex Fermatean Fuzzy (CrC-FFS) decision-making framework and its associated aggregation operators within a WASPAS-based multi-attribute decision-making methodology. It can also serve as a benchmark dataset for developing, testing, and comparing new fuzzy decision-making models and optimization techniques. Dataset Contents Large-scale safety management decision matrix Safety management alternatives Hazard evaluation criteria Circular Complex Fermatean Fuzzy values MATLAB implementation for numerical analysis Supplementary files supporting the research Applications Safety management Industrial hazard risk assessment Emergency response planning Multi-Criteria Decision-Making (MCDM) Advanced fuzzy decision-making Circular Complex Fermatean Fuzzy Sets (CrC-FFS) Intelligent decision support systems Uncertainty modeling Industrial safety optimization Purpose This dataset is publicly available to promote reproducible research, benchmarking, and the development of advanced fuzzy decision-making methodologies for safety management and industrial risk analysis. Researchers may use this dataset to validate newly proposed aggregation operators, ranking methods, optimization algorithms, and MCDM frameworks under uncertain decision environments.