NDLI: Building coal storage centre to settle the problem of power generation coal supply based on KPCA-SVRM

Content Provider	IEEE Xplore Digital Library
Author	Zhang Cai-qing Lu Pan
Copyright Year	2008
Description	Author affiliation: Sch. of Bus. & Adm., North China Electr. Power Univ., Beijing (Zhang Cai-qing; Lu Pan)
Abstract	This paper is established in electricity lines, and put forward the viewpoint that we can build coal storage center to settle the problem of power generation coal supply. Make the coal storage centre site selection by using KPCA (kernel principal component analysis) -SVRM (support vector regression machine), taking all factors into account, and making the advantage of the social division of labor specialization fully played. In KPCA-SVRM, the first step is to apply KPCA to SVRM for feature extraction. KPCA first maps the original inputs into a high dimensional feature space using the kernel method and then calculates PCA in the high dimensional feature space. These new features are then used as the inputs of SVRM to solve the site selection problem. By learning and training, we use the data of this subset to get the solution and find interrelationship of input and output by the SVRM. Practical examples are cited in this paper to illustrate the process.
Starting Page	1609
Ending Page	1613
File Size	402007
Page Count	5
File Format	PDF
ISBN	9781424423873
DOI	10.1109/ICMSE.2008.4669120
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power supplies Power generation economics Conference management site selection coal storage centre KPCA-SVRM Feature extraction Load management power generation coal supply Kernel Energy management Power generation Contracts Principal component analysis
Content Type	Text
Resource Type	Article

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