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http://dx.doi.org/10.5574/KSOE.2012.26.1.060

Estimation of Environmental Costs Based on Size of Oil Tanker Involved in Accident using Neural Network  

Shin, Sung-Chul (Department of Naval Architecture and Ocean Engineering, Pusan National University)
Bae, Jeong-Hoon (Department of Naval Architecture and Ocean Engineering, Pusan National University)
Kim, Hyun-Soo (Department of Naval Architecture and Ocean Engineering, Pusan National University)
Kim, Seong-Hoon (Department of Naval Architecture and Ocean Engineering, Pusan National University)
Kim, Soo-Young (Department of Naval Architecture and Ocean Engineering, Pusan National University)
Lee, Jong-Kap (Maritime & Ocean Engineering Research Institute, KORDI)
Publication Information
Journal of Ocean Engineering and Technology / v.26, no.1, 2012 , pp. 60-63 More about this Journal
Abstract
The accident risks in the marine environment are increasing because of the tendency to build faster and larger ships. To secure ship safety, risk-based ship design (RBSD) was recently suggested based on a formal safety assessment (FSA). In the process of RBSD, a ship designer decides which risk reduction option is most cost-effective in the design stage using a cost-benefit analysis (CBA). There are three dimensions of risk in this CBA: fatality, environment, and asset. In this paper, we present an approach to estimate the environmental costs based on the size of an oil tanker involved in an accident using a neural network. An appropriate neural network model is suggested for the estimation,and the neural network is trained using IOPCF data. Finally,the learned neural network is compared with the cost regression equation by IMO MEPC 62/WP.13 (2011).
Keywords
Neural network; Backpropagation; Risk-based ship design; Oil spill; Cost-benefit analysis;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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