Parameter Reduction in Fuzzy Soft Set Based on Whale Optimization Algorithm
Parameter reduction is one of the hot topics in soft set theory. Deleting redundant parameters can reduce data and make decision effectively. In this article parameter reduction in fuzzy soft sets based on score decision-making method is discussed. The parameter reduction becomes more and more diffi...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/2716035408694791829f9a515d25a633 |
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| Sumario: | Parameter reduction is one of the hot topics in soft set theory. Deleting redundant parameters can reduce data and make decision effectively. In this article parameter reduction in fuzzy soft sets based on score decision-making method is discussed. The parameter reduction becomes more and more difficult with the number of parameters increasing. In order to find reduction quickly, a mathematical model of parameter reduction based on the score decision-making method is constructed, and the whale optimization algorithm is improved and tested. Finally, the reduction is obtained by using the improved whale optimization algorithm. The simulation results show that the method is effective. |
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