NDLI: Sparse online LS-SVM based on modified particle swarm optimization algorithm and application

Content Provider	IEEE Xplore Digital Library
Author	Weiping Zhang Peifeng Niu Guoqiang Li
Copyright Year	2012
Description	Author affiliation: Institute of Electrical Engineering, Yanshan University (Weiping Zhang) \|\| Key Lab of Industrial Computer Control Engineering of Hebei Province (Peifeng Niu) \|\| Institute of Electrical Engineering, Yanshan University, CO 066004 China (Guoqiang Li)
Abstract	In this paper, A simple and effective mechanism is proposed to realize the parsimoniousness of the online least squares support vector machine. Hence, the response time is curtailed. Besides, a modified Particle Swarm Optimization (PSO) algorithm is proposed to ascertain the optimal model parameters. Simulation results show that it outperforms GA and common PSO algorithms and LS-SVM model based on the modified PSO algorithm has the best regression accuracy and generalization ability. The sparse online LS-SVM algorithm is applied to build a turbine heat rate forecasting model, which possesses dynamic prediction functions.
Starting Page	272
Ending Page	276
File Size	877362
Page Count	5
File Format	PDF
ISBN	9781457721441
e-ISBN	9781457721434
DOI	10.1109/ICICIP.2012.6391467
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Support vector machines Computational modeling Heating Prediction algorithms Mathematical model Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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