Referenced Items are not available for this document.
An approach that neural network optimized with PSO algorithm is proposed in the paper. Unlike conventional training method with gradient descent method only, this paper introduces a hybrid training algorithm by combining the PSO and BP algorithm. The PSO is used to optimize the initial parameters of the BP neural network, including the weights and biases. It can effectively better the cases that network is easily trapped to a local optimum and has a slow velocity of convergence. The experiment results show the method in the paper has greater improvement in both accuracy and velocity of convergence for BP neural network.
Published in:
Natural Computation (ICNC), 2010 Sixth International Conference on
(Volume:5
)
Date of Conference: 10-12 Aug. 2010
- Page(s):
- 2520 - 2523
- Print ISBN:
- 978-1-4244-5958-2
- INSPEC Accession Number:
- 11554542
- Conference Location :
- Yantai, Shandong
- Digital Object Identifier :
- 10.1109/ICNC.2010.5583289
- Product Type:
- Conference Publications
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
