Applying Artificial Neural Network Model in Assessing East Dongting Lake Wetland's Ecosystem Carrying Capacity

Because of the superiority in approximation, classification and study speed, the radial basis function artificial neural network (RBF-ANN) model is receiving more and more scholarspsila attention. Its framework, design, simulation and output of graphs are presented. With the aid of MATLAB tools, int...

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Bibliographische Detailangaben
Hauptverfasser: Shi, Y.Z., Xin, D.J.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Because of the superiority in approximation, classification and study speed, the radial basis function artificial neural network (RBF-ANN) model is receiving more and more scholarspsila attention. Its framework, design, simulation and output of graphs are presented. With the aid of MATLAB tools, integrative assessment of regional ecosystem carrying capacity using above model is introduced. As an applied example, the assessment index system including 14 indexes and the standard including 3 levels are constructed for the East Dongting Lake wetland to assess its ecosystem carrying capacity. The result indicates that the ecosystem carrying capacity in studied area belongs to middle-load, which conforms to the local actual situation. In addition, RBF-ANN model is proved to be simple, effective to classify, with strong applicability and broadly-applicable prospect.
DOI:10.1109/ICICTA.2008.412