DocumentCode :
2491671
Title :
Risk assessment in electrical power network planning project based on principal component analysis and support vector machine
Author :
Sun, Wei ; Ma, Yue
Author_Institution :
Dept. of Bus. Adm., Univ. of North China Electr. Power, Baoding
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
5268
Lastpage :
5271
Abstract :
In this paper, a model based on principal component analysis (PCA) and support vector machine (SVM) is used for the risk assessment in the electrical power network planning project to discriminate good projects from bad ones, and a set of comprehensive index system is established here according to the practical situation. In order to verify the effectiveness of the method, a group of actual projects are given and the experimental results show that the model has high correct classification accuracy.
Keywords :
power distribution planning; power engineering computing; power transmission planning; principal component analysis; risk management; support vector machines; comprehensive index system; electrical power network planning project; principal component analysis; risk assessment; support vector machine; Environmental economics; Power generation economics; Power system economics; Power system modeling; Power system planning; Power system reliability; Principal component analysis; Risk management; Support vector machine classification; Support vector machines; Electrical power network planning; Principal component analysis; Risk assessment; Support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593786
Filename :
4593786
Link To Document :
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