Title :
GANN system to optimize both topology and neural weights of a feedforward neural network
Author :
Vizitiu, Iulian-constantin ; Popescu, Florin
Author_Institution :
Commun. & Electron. Syst. Dept., Mil. Tech. Acad., Bucharest, Romania
Abstract :
An interesting approach to improve the quality of the artificial neural network architectures included into a large spectrum of applications, is to use the GANN (Genetic Algorithm Neural Network) system concept. Consequently, a specific genetic technique which simultaneously optimizes both topology and neural weights of a feedforward neural network is described. Finally, to confirm the broached theoretical aspects, a real training database was also used.
Keywords :
feedforward neural nets; genetic algorithms; GANN system; artificial neural network; feedforward neural network; genetic algorithm neural network; neural weights; Artificial neural networks; Bioinformatics; Circuit topology; Databases; Encoding; Feedforward neural networks; Genetic algorithms; Genomics; Network topology; Neural networks; GANN system; feedforward neural network;
Conference_Titel :
Communications (COMM), 2010 8th International Conference on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-6360-2
DOI :
10.1109/ICCOMM.2010.5509105