DocumentCode :
2224358
Title :
Modeling for enterprise energy-consuming process based on LS-SVM and NWFE
Author :
Xu Yong ; Wang Jian
Author_Institution :
CIMS Res. Center, Tongji Univ., Shanghai, China
Volume :
6
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
According to the necessity for researching the optimization of enterprise energy-consuming based on model, the identification method for energy-consuming link in enterprise production process was researched. In view of the existing problems of Least Squares Support Vector Machine (LS-SVM), a modeling method based on nonparametric weighted feature extraction (NWFE) and LS-SVM was proposed. NWFE was applied to intelligent data analysis for extracting typical characteristics from the training samples, and then the data were trained to construct the energy-consuming model based on on-line LS-SVM algorithm. The simulation result showed that the presented modeling method has the advantages of shorter computing time, robust and better generalization ability.
Keywords :
energy consumption; feature extraction; least squares approximations; manufacturing processes; production engineering computing; support vector machines; LS-SVM; NWFE; enterprise energy-consuming process; enterprise production process; intelligent data analysis; least squares support vector machine; nonparametric weighted feature extraction; Chemicals; Computer integrated manufacturing; Kernel; Manufacturing; Support vector machines; Least Squares Support Vector Machine; energy-consuming; nonparametric weighted feature extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579380
Filename :
5579380
Link To Document :
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