Neutrosophic Theories in Intelligent Decision Making, Management and Engineering

Submission Deadline: 22 November 2022 (closed) Submit to Special Issue

Guest Editors

Dr. S. A. Edalatpanah, Ayandegan Institute of Higher Education, Iran.
Dr. Florentin Smarandache, University of New Mexico, United States.
Dr. Dragan Pamučar, University of Defence, Serbia.

Summary

Neutrosophic set is a generalization of fuzzy set and intuitionistic fuzzy set. The key distinction between the neutrosophic set and other types of sets is the introduction of

the degree of indeterminacy / neutrality (I) as independent component in the neutrosophic set.

In the neutrosophic set, the degree of membership-truth (T), the degree of indeterminacy (I), and the degree of non-membership-falsehood (F) are independent, therefore their sum (as single-valued numbers) can be up to 3. Neutrosophic set has been used in solving problems that involve indeterminacy, uncertainty, impreciseness, vagueness, inconsistent, incompleteness, etc. In the past years, the field of neutrosophic set, logic, measure, probability and statistics, pre-calculus and calculus, and their applications in multiple fields have been extended and applied in various fields. For more information, see the University of New Mexico’s website on neutrosophic at: http://fs. [1] unm.edu/neutrosophy.htm [2]. This special issue will provide a systematic overview and state-of-the-art research in the field of neutrosophic set, and will outline new and important developments in fundamentals, approaches, models, methodologies, intelligent decision support systems, and applications in the area of management and engineering.

Scope and Interests (included but not limited to)

• Neutrosophic logic

• Neutrosophic deep learning

• Neutrosophic transportation problems

• Neutrosophic Optimization

• Neutrosophic image processing

• Neutrosophic information processing

• Neutrosophic decision making

• Neutrosophic big data mining

• Neutrosophic decision support systems

• Neutrosophic computational modelling

• Neutrosophic medical diagnosis

• Neutrosophic fault diagnosis

• Artificial intelligence

• Plithogenic sets

• Hybrid neutrosophic sets (rough neutrosophic sets, neutrosophic soft sets…)


Keywords

Neutrosophic sets, plithogenic sets, optimization, decision making, big data, manufacturing, deep learning, image processing.

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