Title: Neural network and PSO-based structural approximation analysis for blade of wind turbine

Authors: Lei Wang; Pin Hu; Jingui Lu; Fengxin Chen; Qi Hua

Addresses: CAD Center, Nanjing University of Technology, Nanjing 210009, China ' CAD Center, Nanjing University of Technology, Nanjing 210009, China ' CAD Center, Nanjing University of Technology, Nanjing 210009, China ' CAD Center, Nanjing University of Technology, Nanjing 210009, China ' CAD Center, Nanjing University of Technology, Nanjing 210009, China

Abstract: Structural approximation analysis is important for optimisation design of blade of wind turbine. The neural network is applied to construct the model of structural approximation analysis for blade of wind turbine in this paper. The approximation analysis on the blade of wind turbine can be performed based on the model of neural network. The back-propagation algorithm and particle swarm optimisation algorithm are applied to train the patterns of approximation analysis for blade of wind turbine, and the neural network-based model can be obtained in this paper. The training procedure of constructing the model of neural network via back-propagation algorithm and particle swarm optimisation algorithm will be discussed in this paper. The numerical example will be given finally in this paper.

Keywords: structural approximation analysis; neural networks; particle swarm optimisation; PSO; turbine blades; wind turbines; wind energy; wind power; design optimisation.

DOI: 10.1504/IJMIC.2013.051936

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.1, pp.69 - 75

Available online: 05 Feb 2013 *

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