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