Optimizing Fuzzy Flip-Flop Based Neural Networks by Bacterial Memetic Algorithm
| Cím | Optimizing Fuzzy Flip-Flop Based Neural Networks by Bacterial Memetic Algorithm |
| Közlemény típusa | Conference Paper |
| Kiadás éve | 2009 |
| Kiadás nyelve | English |
| Oldalszám | 1508-1513 |
| Szerzők | Lovassy, R., L. T. Kóczy, and L. Gál |
| Szerkesztő | Lovassy, R., L. T. Kóczy, and L. Gál |
| Konferencia neve | International Fuzzy Systems Association European Society for Fuzzy Logic and Technology, IFSA |
| Konferencia helyszíne | Lisbon, 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. |