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Optimizing Fuzzy Flip-Flop Based Neural Networks by Bacterial Memetic Algorithm

CímOptimizing Fuzzy Flip-Flop Based Neural Networks by Bacterial Memetic Algorithm
Közlemény típusaConference Paper
Kiadás éve2009
Kiadás nyelveEnglish
Oldalszám1508-1513
SzerzőkLovassy, R., L. T. Kóczy, and L. Gál
SzerkesztőLovassy, R., L. T. Kóczy, and L. Gál
Konferencia neveInternational Fuzzy Systems Association European Society for Fuzzy Logic and Technology, IFSA
Konferencia helyszíneLisbon, Portugal
Összefoglalás

In our previous work we proposed a Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flip-flops (F3) based on various operations. We showed that such kind of fuzzy-neural network had good learning properties. In this paper we propose an evolutionary approach for optimizing fuzzy flip-flop networks (FNN). Various popular fuzzy operation and three different fuzzy flip-flop types will be compared from the point of view of the respective fuzzy-neural networks’ approximation capability.
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