Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps
Dr. W. B. Vasantha Kandasamy, Florentin Smarandache

TL;DR
This paper explores Fuzzy Cognitive Maps and their neutrosophic extension, which incorporate indeterminacy handling, and discusses their diverse applications in modeling complex systems across various fields.
Contribution
It introduces Neutrosophic Cognitive Maps as a generalization of Fuzzy Cognitive Maps, enhancing modeling sensitivity by managing indeterminacy in relationships.
Findings
Neutrosophic Cognitive Maps effectively handle indeterminacy.
FCMs and NCMs are applicable in diverse complex system modeling.
The methods improve decision-making accuracy in various domains.
Abstract
In this book we study the concepts of Fuzzy Cognitive Maps (FCMs) and their Neutrosophic analogue, the Neutrosophic Cognitive Maps (NCMs).Fuzzy Cognitive Maps are fuzzy structures that strongly resemble neural networks, and they have powerful and far-reaching consequences as a mathematical tool for modeling complex systems. Neutrosophic Cognitive Maps are generalizations of FCMs, and their unique feature is the ability to handle indeterminacy in relations between two concepts thereby bringing greater sensitivity into the results. Some of the varied applications of FCMs and NCMs which has been explained by us, in this book, include: modeling of supervisory systems; design of hybrid models for complex systems; mobile robots and in intimate technology such as office plants; analysis of business performance assessment; formalism debate and legal rules; creating metabolic and regulatory…
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Taxonomy
TopicsCognitive Science and Mapping · Multi-Criteria Decision Making · Cognitive Computing and Networks
