DocumentCode
1563437
Title
Multi-scale Wavelet Support Vector Regression for Soft Sensor Modeling
Author
Wang, Jun ; Peng, Hong
Author_Institution
Sch. of Electr. Inf., Xihua Univ., Sichuan
Volume
1
fYear
2005
Firstpage
284
Lastpage
287
Abstract
A new multi-scale wavelet support vector regression (MS-WSVR) for function regression is proposed in this paper, and applied to soft sensor modeling for abamectin fermentation process. Wavelet function with different resolution is used as support vector kernel in order to construct MS-WSVR. Theoretic analysis of the multi-scale wavelet kernel is discussed in detail. Experiments show that this method has better performance than the soft sensor modeling based on the RBF neural network
Keywords
chemical engineering computing; fermentation; neural nets; support vector machines; wavelet transforms; abamectin fermentation process; function regression; multi-scale wavelet support vector regression; soft sensor modeling; support vector kernel; Computer science; Kernel; Mathematical model; Mathematics; Neural networks; Neurofeedback; Process control; Support vector machines; Training data; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614616
Filename
1614616
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