Letters: Evolving artificial neural networks using an improved PSO and DPSO

Authors:
Jianbo Yu;Shijin Wang;Lifeng Xi
Affiliations:
Department of Industrial Engineering and Management, Shanghai Jiaotong University, Shanghai 200240, PR China;Department of Industrial Engineering and Management, Shanghai Jiaotong University, Shanghai 200240, PR China;Department of Industrial Engineering and Management, Shanghai Jiaotong University, Shanghai 200240, PR China
Venue:
Neurocomputing
Year:
2008

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Abstract

This paper presents an improved particle swarm optimization (PSO) and discrete PSO (DPSO) with an enhancement operation by using a self-adaptive evolution strategies (ES). This improved PSO/DPSO is proposed for joint optimization of three-layer feedforward artificial neural network (ANN) structure and parameters (weights and bias), which is named ESPNet. The experimental results on two real-world problems show that ESPNet can produce compact ANNs with good generalization ability.