• DocumentCode
    1628808
  • Title

    Based on Rough Set and Support Vector Machine (SVM) in Jilin Province Power Distribution Network Transformation Project Evaluation

  • Author

    Liu Min ; Zhu Kai ; Cong Li ; Du Qiushi

  • Author_Institution
    Electr. Power Res. Inst., Jilin Electr. Power Co., Ltd., Changchun, China
  • fYear
    2013
  • Firstpage
    202
  • Lastpage
    206
  • Abstract
    In this paper, according to the current status of Jilin province power network construction and transformation projects, established the evaluation index system of power distribution network transformation project. Aiming at the characteristics of the large number of index, proposed a model of evaluating the power distribution network transformation based on rough set and support vector machine (SVM), And uses the evaluate data of the power distribution network in Jilin province for the empirical analysis, shows that the method has higher classification accuracy. The results of the research show that the model has good effectiveness and the method is practical and feasible.
  • Keywords
    distribution networks; power engineering computing; rough set theory; support vector machines; Jilin Province power distribution network transformation project evaluation; SVM; classification accuracy; empirical analysis; evaluation index system; rough set; support vector machine; Accuracy; Indexes; Industries; Power grids; Support vector machines; Training; power distribution network transformation; project evaluation; rough set; support vector machine (SVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing and Applications to Business, Engineering & Science (DCABES), 2013 12th International Symposium on
  • Conference_Location
    Kingston upon Thames, Surrey, UK
  • Type

    conf

  • DOI
    10.1109/DCABES.2013.43
  • Filename
    6636447