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Ugrás a tartalomra

Function Approximation Performance of Fuzzy Neural Networks

CímFunction Approximation Performance of Fuzzy Neural Networks
Közlemény típusaJournal Article
Kiadás éve2010
SzerzőkLovassy, R., L. T. Kóczy, and L. Gál
FolyóiratActa Polytechnica Hungarica, Journal of Applied Sciences
Évfolyam7
Kötet 4
Oldalszám25-38
Kiadás dátuma2010
Kiadás nyelveEnglish
ISSN Number1785-8860
Összefoglalás

In this paper we propose a Multilayer Perceptron Neural Network (MLP NN) consisting of fuzzy flip-flop neurons based on various fuzzy operations applied in order to approximate real life application, two input trigonometric functions furthermore two and six dimensional benchmark problems. The Bacterial Memetic Algorithm with Modified Operator Execution Order algorithm (BMAM) is proposed for Fuzzy Neural Networks (FNN) training. The simulation results showed that various FNN types delivered very good function approximation results.
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