On PSO Based BP Neural Network

Peng Hu; Xiao Quan Song

doi:10.4028/www.scientific.net/AMM.602-605.3518

Paper Titles

A Study of Path Planning Algorithm in VANETs
p.3503

Maximum Likelihood Method for Parameter Estimation of Weibull Distribution Model Based on Fruit Fly Optimization Algorithm
p.3508

A Study on the Image Classification Techniques Based on Wavelet Artificial Neural Network Algorithm
p.3512

RETRACTED: Performance Analysis and Optimization of IEEE 802.11 Protocol
p.3515

On PSO Based BP Neural Network
p.3518

A Study of the Assessment on Air Quality on Fuzzy Comprehensive Index
p.3522

Image Distortion Classification towards Quality Assessment Based on Tri-Training and Natural Scene Statistics
p.3526

Industrial Cluster Competitiveness Connotation and Evaluation - A Case Study of Yulin City Magnesium Industry Clusters
p.3532

Association Rules Optimization Algorithm Based on Fuzzy Clustering
p.3536

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605On PSO Based BP Neural Network

On PSO Based BP Neural Network

Abstract:

Particle swarm optimization (PSO) based BP neural network is introduced , which is superior to the traditional BP neural network . The traditional BP neural network and PSO algorithm is illustrated respectively, and introduces how to apply PSO algorithm in BP neural network. The numerical simulation proves that PSO-BP neural network performs better than traditional BP neural network.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3518-3521

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3518

Citation:

Cite this paper

Online since:

August 2014

Authors:

Peng Hu*, Xiao Quan Song

Keywords:

BP Neural Network (BPNN), Optimization, PSO

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Pan Hao, Hou Qinglan. A BP Networks Learning Algorithm Research based on Particle Swarm Optimizer[J]. Computer Engineering and Applications, 2006, 42(16): 41-43. (in Chinese).

Google Scholar

[2] Han Liqun. Artificial Neural Network Tutoria[M]. Beijing University of Posts and Telecommunications Press, 2006. (in Chinese).

Google Scholar

[3] J. Kennedy and R. Eberhart, Particle Swarm Optimization, Proceedings of IEEE International Conference on Neural Netwroks, Perth, Australia, 1995, (4): 1942-(1948).

Google Scholar

[4] EBERHART R C, SHI Y. Particle swarm optimization: developments, applications and resources[C]. Proceedings of IEEE Congress On Evolutionary Computation. Piscataway NJ: IEEE Press, 2001: 81-86.

DOI: 10.1109/cec.2001.934374

Google Scholar

[5] C. G. Chang, D. W. Wang, Y. C. Liu and B. K. Qi. Application of Particle Swarm Optimization Based BP Neural Network on Engineering Project Risk Evaluating[C]. Proceedings of IEEE Third International Conference on Natural Computation, 2007: 750-754.

DOI: 10.1109/icnc.2007.259

Google Scholar