Citation

Tan, Shing Chiang and Rao, M. V. C. and Lim, Chee Peng (2007) A cooperative learning model for the fuzzy ARTMAP-dynamic decay adjustment network with the genetic algorithm. In: 11th Online World Conference on Soft Computing in Industrial Applications, 18-OCT 06 SEP 2006, ELECTR NETWORK.

Full text not available from this repository.

Abstract

In this paper, combination between a Fuzzy ARTMAP-based artificial neural network (ANN) model and the genetic algorithm (GA) for performing cooperative learning is described. In our previous work, we have proposed a hybrid network integrating the Fuzzy ARTMAP (FAM) network with the Dynamic Decay Adjustment (DDA) algorithm (known as FAMDDA) for tackling pattern classification tasks. In this work, the FAMDDA network is employed as the platform for the GA to perform weight reinforcement. The performance of the proposed system (FAMDDA-GA) is assessed by means of generalization on unseen data from three benchmark problems. The results obtained are analyzed, discussed, and compared with those from FAM-GA. The results reveal that FAMDDA-GA performs better than FAM-GA in terms of test accuracy in the three benchmark problems.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > T Technology (General) Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	06 Oct 2011 07:49
Last Modified:	06 Oct 2011 07:49
URII:	http://shdl.mmu.edu.my/id/eprint/3199

Downloads

Edit (login required)