• DocumentCode
    2995012
  • Title

    Risk assessment in power plants based on AIA improved support vector machines

  • Author

    Sun, Wei ; Zhang, Jie

  • Author_Institution
    Sch. of Bus. Adm., North China Electr. Power Univ., Baoding
  • fYear
    2008
  • fDate
    1-3 Sept. 2008
  • Firstpage
    487
  • Lastpage
    491
  • Abstract
    According to the practical situation of risk assessment in power plants, a set of index system is established. The index system includes financial indexes and non-financial indexes. Then support vector machines (SVM) algorithm is used for assessment in this research. In this paper the step of improve SVM by artificial immune algorithm is given to show how to get the best effectiveness in SVM. In this paper we give an example coming from power plants data and the results show that the method can classify the data effectively, and the model has high correct classification accuracy.
  • Keywords
    artificial immune systems; power plants; risk management; support vector machines; AIA improved support vector machines; artificial immune algorithm; classification accuracy; nonfinancial indexes; power plants; risk assessment; Automation; Logistics; Power generation; Power system modeling; Quadratic programming; Risk management; Statistical learning; Sun; Support vector machine classification; Support vector machines; AIA; Classification; Power plants; Risk assessment; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-2502-0
  • Electronic_ISBN
    978-1-4244-2503-7
  • Type

    conf

  • DOI
    10.1109/ICAL.2008.4636200
  • Filename
    4636200