Authors: Rita Lovassy, Laszlo T. Koczy, Laszlo Gal
Addresses: Institute of Microelectronics and Technology, Kando Kalman Faculty of Electrical Engineering, Obuda University, Tavaszmezo utca 15-17, 1084 Budapest, Hungary. ' Faculty of Engineering Sciences, Szechenyi Istvan University, Egyetem ter 1, 9026 Gyor, Hungary; Department of Telecommunication and Media Informatics, Budapest University of Technology and Economics, Magyar tudosok krt. 2, 1117 Budapest, Hungary. ' Faculty of Engineering Sciences, Szechenyi Istvan University, Egyetem ter 1, 9026 Gyor, Hungary; Department of Technology, Informatics and Economy, University of West Hungary, Karolyi G. ter 4, 9700 Szombathely, Hungary
Abstract: This paper presents a method for optimising the parameters of fuzzy flip-flop-based neural networks (FNN) consisting of fuzzy J-K and D flip-flop neurons based on various popular fuzzy operations using bacterial memetic algorithm with the modified operator execution order (BMAM). In early works, the authors proposed the Levenberg-Marquardt algorithm (LM) a widely used second order gradient type training algorithm for fuzzy neural networks variables optimisation. The BMAM local and global search evolutionary approach is a bacterial type memetic algorithm which executes several LM cycles during the bacterial mutation after each mutational step, using the LM method more efficiently. Numerical experiments were performed to show the function approximation capability of various quasi optimised FNN types based on fuzzy J-K and D flip-flop neurons using algebraic, Lukasiewicz, Yager, Dombi, Hamacher and Frank norms, trained with LM method and BMAM algorithm.
Keywords: fuzzy J-K flip-flop; fuzzy D flip-flop; fuzzy flip-flop neurons; fuzzy flip-flop neural networks; FNN; bacterial memetic algorithms; modified operator execution order; BMAM; mimetics.
International Journal of Reasoning-based Intelligent Systems, 2010 Vol.2 No.3/4, pp.237 - 243
Published online: 12 Nov 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article