Publication Type : Conference Paper
Thematic Areas : Medical Sciences
Publisher : A2CWiC'10
Source : Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore (2010)
ISBN : 9781450301947
Keywords : Algorithms, Artificial Neural Network, Artificial neural networks, Connection weights, Data processing, evolution, Generalization ability, Information processing capability, ITS architecture, Neural networks, Optimized structures, Other algorithms, Particle swarm optimization (PSO), Particle swarm optimization algorithm, Real problems
Campus : Kochi
School : School of Medicine
Department : Respiratory Medicine, Wireless Networks and Applications (AWNA)
Year : 2010
Abstract : The information processing capability of artificial neural networks (ANNs) is closely related to its architecture and connection weights. Various algorithms have been used to get an optimized structure suited for various applications. The paper does a comparative survey on effectiveness of evolving artificial neural networks based on the particle swarm optimization (PSO) algorithm over other algorithms. A description of this type of system tested on real problems in various domains has also been quoted. The results show that ANNs evolved by PSOANN have good accuracy and generalization ability. © 2010 ACM.
Cite this Research Publication : Na Haridas and Devi.M, Nb, “PSO learning on artificial neural networks”, in Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore, 2010.