The Pilot Study on Prediction Method by Artificial Neural Network for Carrying Capacity of Coastal Zone

Author

Li Mingchang ; Zhou Bin ; Liang Shuxiu ; Sun Zhaochen

Author_Institution

Lab. of Environ. Protection in Water Transp. Eng., Tianjin Res. Inst. of Water Transp. Eng., Tianjin, China

fYear

2010

fDate

22-23 May 2010

Firstpage

1

Lastpage

3

Abstract

With the development of the ocean economy exploitation, study on carrying capacity and its dynamic changes are the key methods for all-sided and correct understanding of the relationship between human being and ocean, for scientific management or utilization of ocean resources and realization of ocean sustainable development. This paper presents a Data-Driven Model (DDM) to establish carrying capacity of coastal zone (CCCZ) prediction model solved by artificial neural network. (ANN). The calibration results work well in Liaoning marine zone.

Keywords

aquaculture; neural nets; sustainable development; Liaoning marine zone; artificial neural network; calibration results; carrying capacity; coastal zone; data-driven model; ocean economy exploitation; ocean resources; ocean sustainable development; prediction method; scientific management; Artificial neural networks; Humans; Marine pollution; Nonlinear dynamical systems; Oceans; Prediction methods; Predictive models; Protection; Sea measurements; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5872-1

Electronic_ISBN

978-1-4244-5874-5

Type

conf

DOI

10.1109/IWISA.2010.5473440

Filename

5473440