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