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Initialization by a Novel Clustering for Wavelet Neural Network as Time Series Predictor
Joint Authors
Hu, Hongping
Cheng, Rong
Tan, Xiuhui
Bai, Yanping
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-22
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The architecture and parameter initialization of wavelet neural network are discussed and a novel initialization method is proposed.
The new approach can be regarded as a dynamic clusteringprocedure which will derive the neuron number as well as the initial value of translation and dilation parameters according to the input patterns and the activating wavelets functions.
Three simulation examples are given to examine the performance of our method as well as Zhang's heuristic initialization approach.
The results show that the new approach not only can decide the WNN structure automatically, but also provides superior initial parameter values that make the optimization process more stable and quickly.
American Psychological Association (APA)
Cheng, Rong& Hu, Hongping& Tan, Xiuhui& Bai, Yanping. 2015. Initialization by a Novel Clustering for Wavelet Neural Network as Time Series Predictor. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057719
Modern Language Association (MLA)
Cheng, Rong…[et al.]. Initialization by a Novel Clustering for Wavelet Neural Network as Time Series Predictor. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1057719
American Medical Association (AMA)
Cheng, Rong& Hu, Hongping& Tan, Xiuhui& Bai, Yanping. Initialization by a Novel Clustering for Wavelet Neural Network as Time Series Predictor. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057719
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057719