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A new Cuckoo Search Based Levenberg-Marquardt (CSLM) algorithm

Mohd Nawi, Nazri and Khan, Abdullah and Rehman, Mohammad Zubair (2013) A new Cuckoo Search Based Levenberg-Marquardt (CSLM) algorithm. In: International Conference on Computational Science and Its Applications (ICCSA 2013), 24-27 June 2013, Ho Chi Minh City.

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Abstract

Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural networks. It is also a very popular optimization procedure applied to find optimal weights in a training process. However, traditional back propagation optimized with Levenberg marquardt training algorithm has some drawbacks such as getting stuck in local minima, and network stagnancy. This paper proposed an improved Levenberg-Marquardt back propagation (LMBP) algorithm integrated and trained with Cuckoo Search (CS) algorithm to avoided local minima problem and achieves fast convergence. The performance of the proposed Cuckoo Search Levenberg-Marquardt (CSLM) algorithm is compared with Artificial Bee Colony (ABC) and similar hybrid variants. The simulation results show that the proposed CSLM algorithm performs better than other algorithm used in this study in term of convergence rate and accuracy.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: artificial neural network; back propagation; local minima; Levenberg-Marquardt; cuckoo search algorithm
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 11 Jul 2013 02:36
Last Modified: 21 Jan 2015 08:07
URI: http://eprints.uthm.edu.my/id/eprint/4004
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