TY - JOUR
T1 - Application of artificial neural network in complex systems of regional sustainable development
AU - Shi, Chun
AU - James, Philip
AU - Guo, Zhong Yang
PY - 2004
Y1 - 2004
N2 - 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.
AB - 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.
KW - Artificial neural network
KW - Complex systems
KW - Regional development
KW - Sustainable development
UR - https://www.scopus.com/pages/publications/16544391813
U2 - 10.1007/s11769-004-0001-7
DO - 10.1007/s11769-004-0001-7
M3 - 文章
AN - SCOPUS:16544391813
SN - 1002-0063
VL - 14
SP - 1
EP - 8
JO - Chinese Geographical Science
JF - Chinese Geographical Science
IS - 1
ER -