Publication Type:

Conference Paper

Source:

Proceedings of the 1st Amrita ACM-W Celebration of Women in Computing in India, A2CWiC'10, Coimbatore (2010)

ISBN:

9781450301947

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-78649422791&partnerID=40&md5=b07a95a0490107798d4ed59a9e1de094

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

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.

Notes:

cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@5c92436e ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@6891a3d Through org.apache.xalan.xsltc.dom.DOMAdapter@13199e25; Conference Code:82507

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.