Synthesis of neural tree models by improved breeder genetic programming |
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Authors: | Feng Qi Xiyu Liu Yinghong Ma |
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Affiliation: | (1) School of Management and Economics, Shandong Normal University, Jinan, China |
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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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Keywords: | |
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