A Hybrid of Cuckoo Search and Simplex Method for Fuzzy Neural Network Training

Jyh-Yeong Chang, Shih-Hui Liao, Shang-Lin Wu, Chin-Teng Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


In this paper, a new hybrid algorithm mixing the simplex method of Nelder and Mead (NM) and the cuckoo search (CS), abbreviated as NM-CS, is proposed for the training of the Fuzzy Neural Networks (FNNs). In standard CS, cuckoo birds engage the obligate brood parasitism by laying their own eggs to other host birds. If a host bird discovers the alien eggs, they will either throw these eggs away or abandon its nest and build a new nest elsewhere. In the proposed hybrid algorithm, instead of using the probability to discover an alien egg for the CS, we use the concept of a simplex which is used in the NM algorithm to abandon and generate the new nests. Our proposed method puts more emphasis on exploration of the search space and enhances the ability to avoid local optimum. Some simulation problems will be provided to compare the performances of the proposed method and other methods in training an FNN. In these simulations, it is observed that the proposed method outperforms other methods.
Original languageEnglish
Title of host publicationIEEE 12th International Conference on Networking, Sensing and Control
Number of pages4
StatePublished - 2015


  • Cuckoo Search (CS); simplex method of Nelder and Mead (NM); Fuzzy Neural Network (FNN)

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