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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 273A Hybrid Optimization Method for Neural Tree...

A Hybrid Optimization Method for Neural Tree Network Model

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Abstract:

Neural tree network model has been successfully applied to solving large numbers of complex nonlinear problems in control area. The optimization of neural tree model contains: structure and parameter, the major problem in evolving structure without parameter information was noisy fitness evaluation problem, so an improved genetic programming algorithm is proposed to synthesize the optimization process. Simulation results on two time series prediction problems show that the proposed strategy is a potential method with better performance and effectiveness.

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Periodical:

Applied Mechanics and Materials (Volume 273)

Pages:

820-825

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.273.820

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Online since:

January 2013

Authors:

Feng Qi, Ying Hong Ma, Xi Yu Liu

Keywords:

Exponential Mutation, Fitness Evaluation, Improved Hybrid Breeder Genetic Programming, Neural Tree Network Model, Time Series Forecasting

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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