A hybrid neural network model for noisy data regression

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
Eric W M LeeS M Lo

Abstract

A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning systems and are very fast in network training. The proposed hybrid model, denoted as GRNNFA, is able to retain these advantages and, at the same time, to reduce the computational requirements in calculating and storing information of the kernels. A clustering version of the GRNN is designed with data compression by FA for noise removal. An adaptive gradient-based kernel width optimization algorithm has also been devised. Convergence of the gradient descent algorithm can be accelerated by the geometric incremental growth of the updating factor. A series of experiments with four benchmark datasets have been conducted to assess and compare effectiveness of GRNNFA with other approaches. The GRNNFA model is also employed in a novel application task for predicting the evacuation time of patrons at typical karaoke centers in Hong Kong in the event of fire. The results positively demonstrate the applicability of GRNNFA in noisy data regression problems.

References

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Citations

Sep 13, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Buse Melis Ozyildirim, Mutlu Avci
Jan 10, 2013·Neural Networks : the Official Journal of the International Neural Network Society·Buse Melis Ozyildirim, Mutlu Avci
Nov 12, 2015·Neural Networks : the Official Journal of the International Neural Network Society·Buse Melis Ozyildirim, Mutlu Avci
Jun 10, 2006·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Alfonso C Martínez-EstudilloNicolás García-Pedrajas
Sep 10, 2008·IEEE Transactions on Neural Networks·Keem Siah YapIzham Zainal Abidin
Dec 7, 2007·IEEE Transactions on Neural Networks·John Y GoulermasPhil Cook
Dec 5, 2008·IEEE Transactions on Neural Networks·Jiann-Ming Wu
Jan 9, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·John Y GoulermasJason F Ralph
Mar 13, 2008·IEEE Transactions on Neural Networks·Chi-Sing Leung, John Pui-Fai Sum

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