Mayfly Algorithm with Automatic Parameter Adaptation with Fuzzy Logic
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67195-1_49
Reference21 articles.
1. Valdez, F., Vazquez, J. C., Gaxiola, F.: Fuzzy Dynamic Parameter Adaptation in ACO and PSO for Designing Fuzzy Controllers: The Cases of Water Level and Temperature Control. Adv. Fuzzy Syst. 2018 (2018). https://doi.org/10.1155/2018/1274969
2. Li, H., Yang, H., Zhang, L., Huang, X., Wang, H., Kang, Y.: Improved discrete mayfly algorithm for multi-objective dynamic network community detection. J. Front. Comput. Sci. Technol. 17(4), 942–952 (2023). https://doi.org/10.3778/j.issn.1673-9418.2106011
3. Zervoudakis, K., Tsafarakis, S.: A mayfly optimization algorithm. Comput. Ind. Eng. 145 (2020). https://doi.org/10.1016/j.cie.2020.106559
4. Melin, P., Olivas, F., Castillo, O., Valdez, F., Soria, J., Valdez, M.: Optimal design of fuzzy classification systems using PSO with dynamic parameter adaptation through fuzzy logic. Expert Syst. Appl. 40(8), 3196–3206 (2013). https://doi.org/10.1016/j.eswa.2012.12.033
5. Guerrero, M., Valdez, F., Castillo, O.: Comparative Study between Type-1 and Interval Type-2 Fuzzy Systems in Parameter Adaptation for the Cuckoo Search Algorithm. Symmetry (Basel) 14(11) (2022). https://doi.org/10.3390/sym14112289
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