DocumentCode :
2559454
Title :
Research on comprehensive carrying capacity assessment method with data-driven neural network
Author :
Si Qi ; Li Mingchang ; Zhang Guangyu ; Liang Shuxiu ; Sun Zhaochen
Author_Institution :
Lab. of Environ. Protection in Water Transp. Eng., Tianjin Res. Inst. of Water Transp. Eng., Tianjin, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
458
Lastpage :
460
Abstract :
With the development of the exploitation in Tianjin coastal District, study on carrying capacity and its dynamic changes are the key methods for improving the scientific management level and for realizing sustainable development. This paper presents a data-driven neural network method to establish comprehensive carrying capacity assessment model by the nonlinear relationship between impact factors and level of carrying capacity. The calibration results work well in Tianjin Binhai District.
Keywords :
environmental management; neural nets; sustainable development; Tianjin coastal district; calibration results; comprehensive carrying capacity assessment method; data-driven neural network method; impact factors; nonlinear relationship; scientific management level; sustainable development; Artificial neural networks; Biological system modeling; Economic indicators; Indexes; Neurons; Sea measurements; Assessment; Carrying capacity; Data-driven; Neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234683
Filename :
6234683
Link To Document :
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