DOI Number : 10.5614/itbj.ict.res.appl.2013.7.2.1
Hits : 7

CSLM: Levenberg Marquardt based Back Propagation Algorithm Optimized with Cuckoo Search

Nazri Mohd. Nawi, Abdullah Khan & M. Z. Rehman

Software and Multimedia Centre, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM).
P.O. Box 101, 86400 Parit Raja, BatuPahat, Johor DarulTakzim, Malaysia
Email: hi100010@siwa.uthm.edu.my


Abstract. Training an artificial neural network is an optimization task, since it is desired to find optimal weight sets for a neural network during training process. Traditional training algorithms such as back propagation have some drawbacks such as getting stuck in local minima and slow speed of convergence. This study combines the best features of two algorithms; i.e. Levenberg Marquardt back propagation (LMBP) and Cuckoo Search (CS) for improving the convergence speed of artificial neural networks (ANN) training. The proposed CSLM algorithm is trained on XOR and OR datasets. The experimental results show that the proposed CSLM algorithm has better performance than other similar hybrid variants used in this study.

Keywords: artificial neural networks; back propagation; cuckoo search; levenberg marquardt; local minima.

Download Article
 
Bahasa Indonesia | English
 
 
 

Notification:

Begin on 10 October 2014 this website is no longer activated for article process in Journal of Mathematical and Fundamental Sciences, Journal of Engineering and Technological Sciences, Journal of ICT Research and Applications and Journal of Visual Art and Design. The next process will be proceeded under new website at http://journals.itb.ac.id.

For detail information please contact us to: journal@lppm.itb.ac.id.

 
       
       
       ITB Journal Visitor Number #24093830       
       Jl. Tamansari 64, Bandung 40116, Indonesia Visitor IP Address #       
       Tel : +62-22-250 1759 ext. 121 © 2011 Institut Teknologi Bandung       
       Fax : +62-22-250 4010, +62-22-251 1215 XHTML + CSS + RSS       
       E-mail : journal@lppm.itb.ac.id or proceedings@lppm.itb.ac.id Developed by AVE