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Research on Evaluating Algorithms for the Service Quality of Wireless Sensor Networks Based on Interval-Valued Intuitionistic Fuzzy EDAS and CRITIC Methods

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  • Shihui Li
  • Bo Wang

Abstract

Wireless sensor networks play an important role in economic production and social life. However, in recent years, the number of wireless sensor network vulnerabilities has been increasing rapidly, which makes wireless sensor networks face more and more severe challenges. It is of great significance to realize the quantitative evaluation of wireless sensor networks in order to maintain the service quality of wireless sensor networks more effectively. The evaluating problem of the service quality of wireless sensor networks is a kind of multiple attribute group decision-making (MAGDM) problem. In this paper, depending on the classical EDAS method, the EDAS method will be extended to interval-valued intuitionistic fuzzy sets (IVIFSs) to address some MAGDM issues. At first, some essential concepts of IVIFSs are briefly reviewed. Subsequently, relying on the CRITIC method, the attributes’ weights are decided. Furthermore, integrating the EDAS method with IVIFSs, IVIF-EDAS method is established, and all calculating procedures are depicted. Finally, an empirical application for evaluating the service quality of wireless sensor networks is given to demonstrate this novel algorithm, and some comparative analyses are made to confirm the merits of the designed method.

Suggested Citation

  • Shihui Li & Bo Wang, 2020. "Research on Evaluating Algorithms for the Service Quality of Wireless Sensor Networks Based on Interval-Valued Intuitionistic Fuzzy EDAS and CRITIC Methods," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, July.
  • Handle: RePEc:hin:jnlmpe:5391940
    DOI: 10.1155/2020/5391940
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    Cited by:

    1. Melda Kokoç & Süleyman Ersöz, 2021. "A literature review of interval-valued intuitionistic fuzzy multi-criteria decision-making methodologies," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(4), pages 89-116.

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