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A new levenberg marquardt based back propagation algorithm trained with cuckoo search

Mohd Nawi, Nazri and Khan, Abdullah and Rehman, Mohammad Zubair (2013) A new levenberg marquardt based back propagation algorithm trained with cuckoo search. In: 4th International Conference on Electrical Engineering and Informatics (ICEEI 2013), 24-25 June 2013, Universiti Kebangsaan Malaysia.

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Abstract

Back propagation training algorithm is widely used techniques in artificial neural network and is also very popular optimization task in finding an optimal weight sets during the training process. However, traditional back propagation algorithms have some drawbacks such as getting stuck in local minimum and slow speed of convergence. This research proposed an improved Levenberg Marquardt (LM) based back propagation (BP) trained with Cuckoo search algorithm for fast and improved convergence speed of the hybrid neural networks learning method. The performance of the proposed algorithm is compared with Artificial Bee Colony (ABC) and the other hybridized procedure of its kind. The simulation outcomes show that the proposed algorithm performed better than other algorithm used in this study in term of convergence speed and rate.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: artificial neural network; back propagation; local minima; levenberg marquardt; cuckoo search
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: 28 Aug 2013 03:22
Last Modified: 28 Aug 2013 03:22
URI: http://eprints.uthm.edu.my/id/eprint/4093
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