• DocumentCode
    2451735
  • Title

    Evaluation Model Analysis of the Control Efficiency of Environmental Resource Regulation

  • Author

    Wang Linxiu ; Cheng Kun

  • Author_Institution
    Sch. of Archit. & Civil Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2009
  • fDate
    25-26 April 2009
  • Firstpage
    788
  • Lastpage
    793
  • Abstract
    The exterior of Environmental resources decide that the Energy consumption and reducing pollutant emissions can restrict and improve the way of Production and life by means of energy and environmental control policy. Because the existing environmental policy can not restrain the over-consumption of energy and deteriorating environmental situation phenomenon fundamentally, we establish a BP neural network model to predict the timeliness of policies. In order to guide enterprises to take the initiative to implement cleaner production better and achieve China´s economy sustainable development, in the model, we point out the two-covariate variance method of testing Multi-control policypsilas effectiveness, which can provide a reference for governments at all levels to develop and improve the various of environment and energy regulation.
  • Keywords
    backpropagation; covariance matrices; environmental science computing; neural nets; sustainable development; BP neural network; cleaner production; energy consumption; energy regulation; environmental control policy; environmental resource regulation; evaluation model analysis; multicontrol policy effectiveness; pollutant emission reduction; pollutant emissions; sustainable development; Civil engineering; Economic forecasting; Environmental economics; Government; Neural networks; Pollution; Power generation economics; Predictive models; Production; Testing; BP neural network; Cluster Analysis; control policy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
  • Conference_Location
    Hainan Island
  • Print_ISBN
    978-0-7695-3615-6
  • Type

    conf

  • DOI
    10.1109/JCAI.2009.145
  • Filename
    5159121