Journal
NEUROCOMPUTING
Volume 69, Issue 4-6, Pages 449-465Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2005.02.006
Keywords
local linear wavelet neural networks; particle swarm optimization algorithm; gradient descent algorithm; time-series prediction
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A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weights between the hidden layer and output layer of conventional WNN are replaced by a local linear model. A hybrid training algorithm of particle swarm optimization (PSO) with diversity learning and gradient descent method is introduced for training the LLWNN. Simulation results for the prediction of time-series show the feasibility and effectiveness of the proposed method. (c) 2005 Elsevier B.V. All rights reserved.
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