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SHI Chun, Philip JAMES, GUO Zhong-yang. APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT[J]. Chinese Geographical Science, 2004, 14(1): 1-8.
Citation: SHI Chun, Philip JAMES, GUO Zhong-yang. APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT[J]. Chinese Geographical Science, 2004, 14(1): 1-8.
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APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT

  • 1.

    Departrment of Geography, School of Resources and Environmental Science/Key Laboratory of Geographical Information Science, East China Normal University, Shanghai 200062, P. R. China;

  • 2.

    Telford Institute of Environmental Systems, School of Environment and Life Sciences, University of Salford, Salford M6 6PU, UK

  • Received Date: 2003-09-09
  • Publish Date: 2004-03-20
  • Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT

  • 1. Departrment of Geography, School of Resources and Environmental Science/Key Laboratory of Geographical Information Science, East China Normal University, Shanghai 200062, P. R. China;
  • 2. Telford Institute of Environmental Systems, School of Environment and Life Sciences, University of Salford, Salford M6 6PU, UK
  • Received Date: 2003-09-09
  • Publish Date: 2004-03-20

Abstract: Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.

SHI Chun, Philip JAMES, GUO Zhong-yang. APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT[J]. Chinese Geographical Science, 2004, 14(1): 1-8.
Citation: SHI Chun, Philip JAMES, GUO Zhong-yang. APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT[J]. Chinese Geographical Science, 2004, 14(1): 1-8.
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