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期刊论文

Evolving Flexible Neural Networks Using Ant Programming and PSO Algorithm

杨波Yuehui Chen Bo Yang and Jiwen Dong

F. Yin, J. Wang, and C. Guo (2004)211-216,-0001,():

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摘要/描述

A flexible neural network (FNN) is a multilayer feedforward neural network with the characteristics of: (1) overlayer connections; (2) variable activation functions for different nodes and (3) sparse connections between the nodes. A new approach for designing the FNN based on neural tree encoding is proposed in this paper. The approach employs the ant programming (AP) to evolve the architecture of the FNN and the particle swarm optimization (PSO) to optimize the parameters encoded in the neural tree. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with the related methods.

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版权说明:以下全部内容由杨波上传于   2009年09月28日 09时13分40秒,版权归本人所有。

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