• DocumentCode
    480628
  • Title

    Quantitative Assessment and Prediction for Industrial Economy Development Stress on Eco-Environment

  • Author

    Wang, Qi

  • Author_Institution
    Sch. of Life & Environ. Sci., Wenzhou Univ., Wenzhou
  • Volume
    2
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    531
  • Lastpage
    535
  • Abstract
    The industrial economy has a tremendous impact on the ecological environment. A three-layer artificial neural network (ANN) models were developed to predict industrial economic development stress on eco-environment. The results showed that ESI was the highest in 1997, whereas ESI was the lowest in 1998. ESI in different years has fluctuated, but all belong to fourth level, representing higher eco-environment pressure. Standardization transformation is the best among square root transformation, standardization transformation and natural logarithm transformation. From a short-term forecasting viewpoint, the ANN based on BP algorithm yielded the lowest of average MAPE from 1997 to 2004. The artificial neural network models are useful tool for evaluation and prediction for industrial economy development stress on eco-environment and may be applicable to prediction of other ecological regions.
  • Keywords
    ecology; industrial economics; industrial waste; neural nets; standardisation; sustainable development; BP algorithm; ecological environment; industrial economy development stress; quantitative assessment; standardization transformation; three-layer artificial neural network; Artificial neural networks; Biological system modeling; Economic forecasting; Environmental economics; Industrial economics; Industrial relations; Predictive models; Standardization; Stress; Sustainable development; Artificial neural network; Eco-environment stress index; Industrial economy; Standardization transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.471
  • Filename
    4739821