WSN Clustering using Fuzzy Logic for Increase in Residual Energy

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Description

Machine learning based WSN configuration is presented in this work. The features selection is done by the GWO algorithm and machine learning based fuzzy logic system is used for the classification. Machine learning based GWO tuned Fuzzy logic system minimize the residual energy.

Published Paper similar to this work

The employment of this code in these research publications is beneficial.

  1. Bhalaji, N. “Cluster Formation using Fuzzy Logic in Wireless Sensor Networks.” IRO Journal on Sustainable Wireless Systems 3, no. 1 (2021): 31-39.
  2. Pawar, Atul, Mihir Mondhe, Pranav Kharche, Shrutik Manwatkar, and Ganesh Dhore. “Energy-Efficient Cluster Formation for Wireless Sensor Networks Using Fuzzy Logic.” In Intelligent Sustainable Systems, pp. 657-665. Springer, Singapore, 2022.
  3. Al-Husain, Enaam A., and Ghaida A. Al-Suhail. “E-FLEACH: An Improved Fuzzy Based Clustering Protocol for Wireless Sensor Network.” (2021).
  4. Rana, Tanisha, Avik Sett, Kunal Biswas, and Tufan Saha. “Fuzzy-Based Clustering Toward Improving the Lifespan of Wireless Sensor Networks.” In Proceedings of International Conference on Advanced Computing Applications, pp. 369-380. Springer, Singapore, 2022.
  5. Jayaraman, Ganesh, and V. R. Dhulipala. “FEECS: Fuzzy-Based Energy-Efficient Cluster Head Selection Algorithm for Lifetime Enhancement of Wireless Sensor Networks.” Arabian Journal for Science and Engineering (2021): 1-11.

 

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