An Approach for Study of Traffic Congestion Problem Using Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps-the Case of Indian Traffic

Authors

  • Sujatha Ramalingam Department of Mathematics;SSN College of Engineering; Chennai; India
  • Kuppuswami Govindan Department of Mathematics; Sri Venkateswaraa College of Technology; Chennai; India
  • W.B. Vasantha Kandasamy Department of Mathematics;School of Computer Science and Engineering;VIT University;India
  • Said Broumi Laboratory of Information Processing;Faculty of Science Ben M’Sik, University Hassan II; Casablanca; Morocco

Keywords:

Fuzzy Cognitive Maps, Neutrosophic Cognitive Maps, Traffic congestion problem, Connection matrix

Abstract

The aim of this paper is to find the reasons for traffic congestion problem and its solution using Neutrosophic Cognitive Maps (NCMs) and Fuzzy Cognitive Maps (FCMs). Fuzzy theory only measures the grade of membership but fuzzy theory has failed to characteristic the perception when the relations between concepts in problems are indeterminate. Addition of concepts of indeterminate situation with fuzzy logic forms the neutrosophic logic. Since, some of the reasons for traffic congestions are indeterminate we use Neutrosophic Cognitive Maps to find a solution. The discussion is based on Indian road scenario.

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Published

2019-12-10

Issue

Vol. 30 (2019): Neutrosophic Sets and Systems

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

 Creative Commons Attribution (CC BY) license.

How to Cite

Ramalingam, S. ., Govindan, K. ., Kandasamy, . W. V. ., & Broumi, S. (2019). An Approach for Study of Traffic Congestion Problem Using Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps-the Case of Indian Traffic. Neutrosophic Sets and Systems, 30, 273-283. https://fs.unm.edu/nss8/index.php/111/article/view/456