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Neural Computing and Applications

Erschienen in:

01.04.2012 | Original Article

Synthesis of neural tree models by improved breeder genetic programming

verfasst von: Feng Qi, Xiyu Liu, Yinghong Ma

Erschienen in: Neural Computing and Applications | Ausgabe 3/2012

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Abstract

Neural tree model has been successfully applied to solving a variety of interesting problems. In most previous studies, optimization of the neural tree model was divided into two steps: first structure optimization, then parameter optimization. One major problem in the evolution of structure without parameter information was noisy fitness evaluation. In this paper, an improved breeder genetic programming algorithm is proposed to the synthesis of neural tree model. The effectiveness and performance of the method are evaluated on time series prediction problems and compared with those of related methods. Simulation results show that the proposed algorithm is a potential method with better performance and effectiveness.

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Titel: Synthesis of neural tree models by improved breeder genetic programming
verfasst von: Feng Qi
Xiyu Liu
Yinghong Ma
Publikationsdatum: 01.04.2012
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 3/2012
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-010-0451-z

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