NDLI: An Analysis Of PSO Hybrid Algorithms For Feed-Forward Neural Networks Training

Content Provider	IEEE Xplore Digital Library
Author	Carvalho, Marcio Ludermir, Teresa B.
Copyright Year	2006
Description	Author affiliation: Federal University of Pernambuco, Brazil (Carvalho, Marcio; Ludermir, Teresa B.)
Abstract	Training neural networks is a complex task of great importance in problems of supervised learning. The Particle Swarm Optimization (PSO) consists of a stochastic global search originated from the attempt to graphically simulate the social behavior of a flock of birds looking for resources. In this work we analyze the use of the PSO algorithm and two variants with a local search operator for neural network training and investigate the influence of the GL_5 stop criteria in generalization control for swarm optimizers. For evaluating these algorithms we apply them to benchmark classification problems of the medical field. The results showed that the hybrid PSO with local search operator had the best results among the particle swarm optimizers and that the GL_5 stop criteria almost always degraded the performance of population based optimizers.
Starting Page	6
Ending Page	11
File Size	324255
Page Count	6
File Format	PDF
ISBN	0769526802
DOI	10.1109/SBRN.2006.10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-23
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Feedforward systems Neural networks Feedforward neural networks Particle swarm optimization Artificial neural networks Convergence Simulated annealing Ant colony optimization Supervised learning multi-layer perceptron. Artificial neural network training particle swarm optimization hybrid systems
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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