DocumentCode :
477475
Title :
Applying Artificial Neural Network Model in Assessing East Dongting Lake Wetland´s Ecosystem Carrying Capacity
Author :
Shi, Y.Z. ; Xin, D.J.
Author_Institution :
Sch. of Water Conservancy, Changsha Univ. of Sci. & Technol., Changsha
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
179
Lastpage :
182
Abstract :
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.
Keywords :
ecology; geophysics computing; lakes; radial basis function networks; East Dongting Lake wetland ecosystem; MATLAB tools; RBF-ANN; artificial neural network model; radial basis function artificial neural network; regional ecosystem; Artificial intelligence; Artificial neural networks; Automation; Computer networks; Ecosystems; Gaussian processes; Intelligent networks; Lakes; MATLAB; Mathematical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.412
Filename :
4659467
Link To Document :
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