Time-series prediction using a local linear wavelet neural network
Time-series prediction using a local linear wavelet neural network
复制标题
使用局部线性小波神经网络进行时间序列预测
DOI：
10.1016/j.neucom.2005.02.006
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发表时间：
2006-01-01
期刊：
影响因子：
6
通讯作者：
Dong, JW
中科院分区：
文献类型：
--
作者：
Chen, YH;Yang, B;Dong, JW
提出了一种局部线性小波神经网络。该网络与传统小波神经网络的不同之处在于，用局部线性模型代替了传统小波神经网络隐含层和输出层之间的连接权。针对LLWNN的训练问题，提出了一种多样性学习与梯度下降相结合的粒子群优化混合训练算法。对时间序列进行预测的仿真结果表明了该方法的可行性和有效性。(C)2005 Elsevier B.V.保留所有权利。
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.