NDLI: The investing risk comprehensive evaluation using an improved support vector machine algorithm

Content Provider	IEEE Xplore Digital Library
Author	Zhi-Bin Liu Peng Shen
Copyright Year	2008
Description	Author affiliation: Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding (Zhi-Bin Liu)
Abstract	The electric power projects face the uncertain external environment, they are complex of projects themselves and the ability of the designers, erectors and operators are limited, which make the investing risk evaluation of electric power project becomes a pressing settlement problem. To evaluate the investing risk scientifically and accurately, this paper proposes the multi-level classification evaluating model based on improved support vector machine (SVM), which uses the SVM classification combination in series and introduces the type weight factor and sample weight factor. The model not only solves the shortcomings of small sample, high dimension, nonlinear and local minima in the traditional model, but solves the wrong classification question caused by the number imbalance of training samples and data interference. The investment risk evaluating results of 14 electric power projects in National Power Company show that the model is simple, feasible, and improve the evaluating accuracy and efficiency.
Starting Page	1484
Ending Page	1488
File Size	390221
Page Count	5
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Power systems Training Artificial neural networks Machine learning Biological system modeling Decision making Electric power projects Support vector machine Investing risk Comprehensive evaluating
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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