Interval-Valued Fermatean Quadripartitioned Neutrosophic Similarity Model for Real-Time Safety Evaluation in Electrical Automation Systems
Keywords:
Electrical Automation Safety; Interval-Valued Fermatean Neutrosophic Set; Quadripartitioned Neutrosophic Model; Safety Evaluation; Similarity Measure; Subtraction Algebra; Real-Time Decision Making; Uncertainty Modeling.Abstract
Electrical automation systems operate in dynamic environments where sensor
data are often imprecise, contradictory, or incomplete. Traditional safety evaluation
approaches struggle to cope with this complexity, especially under real-time constraints.
This paper introduces a novel mathematical framework based on Interval-Valued
Fermatean Quadripartitioned Neutrosophic Sets (IVFQNS) for modeling and evaluating
safety conditions in electrical automation systems. The proposed model captures four
distinct cognitive states: truth, falsity, contradiction, and ignorance, each expressed as
interval-valued degrees to reflect uncertainty more effectively. A new similarity measure
tailored for IVFQNS is developed to compare the current system state with a predefined
ideal safety state. The model is integrated into a structured decision-making framework
suitable for real-time environments. A complete case study on an industrial automation
scenario demonstrates the model’s capacity to handle uncertainty, provide quantitative
safety assessment, and support timely decision-making. Results validate the model’s
mathematical consistency, interpretability, and practical relevance.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
