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- W3148851985 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 optimi- zation, 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 per- formance of the method are evaluated on time series pre- diction problems and compared with those of related methods. Simulation results show that the proposed algo- rithm is a potential method with better performance and effectiveness." @default.
- W3148851985 created "2021-04-13" @default.
- W3148851985 creator A5040866480 @default.
- W3148851985 date "2012-01-01" @default.
- W3148851985 modified "2023-09-27" @default.
- W3148851985 title "Synthesis of neural tree models by improved breeder genetic programming" @default.
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