Penggunaan Algoritma Genetika untuk Optimasi Jaringan Neural Buatan-Fuzzy dan Aplikasinya pada Sistem Penciuman Elektronik
Ponix Irwanto, Benyamin Kusumoputro · DOAJ (DOAJ: Directory of Open Access Journals) · 2002
In this article we proposed a method for optimizing the structure of a fuzzy artifi cial neural networks (FANN) through genetic algorithms. This genetic algorithm (GA) is used to optimize the number of weight connections in a neural network structure, by evolutionary calculating the fi tness function of those structures as individuals in a population. This fuzzy neural is then applied as the pattern recognition in our developed odor recognition system. Experimental results show that the optimized neural system provides higher recognition capability compare with that of unoptimized neural system. Recognition rate of the unoptimized neural structure is 70.4% and could be increased up to 85.2% in the optimized neural system. It is also shown that the computational cost of the optimized structure of neural system is also lower than the unoptimized structure.