• DocumentCode
    3302329
  • Title

    The Risk Assessment Model of Special Equipment Based on F-AHP and ANN

  • Author

    Zhang, Guang-ming ; Qiu, Chun-ling ; Li, Xiang-dong ; Zhu, Wei

  • Author_Institution
    Coll. of Autom., Nanjing Univ. of Technol., Nanjing
  • Volume
    3
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    540
  • Lastpage
    545
  • Abstract
    Special equipments mean equipments that are dangerous and relating to lives such as boiler, pressure container, elevator, crane, and the passenger ropeways. The method of weighted average analysis is used in the artificial neural network (ANN) model of the risk assessment for special equipments. In this method the adopted weights are all based on expert experience, so the assessment time is too long. So a risk assessment model based on fuzzy analytic hierarchy process (F-AHP) and ANN is proposed. Firstly, to carry on the level analysis to all possible influences factor using the F-AHP method; calculates the weight of each influence factor which occupies in the influence special equipment safe state; then according to the weight choose the most influential factor as the input of ANN model. Finally use the risk assessment model on the elevator, the assessment time used is less than former ANN model, and the accuracy is not less than former ANN model.
  • Keywords
    fuzzy set theory; neural nets; risk management; safety; ANN; artificial neural network; boiler; cranes; elevators; fuzzy analytic hierarchy process; passenger ropeways; pressure container; risk assessment model; Accidents; Artificial neural networks; Boilers; Containers; Cranes; Elevators; Neurons; Risk analysis; Risk management; Safety devices; ANN; F-AHP; Risk assessment; Special Equipment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.122
  • Filename
    4667197