Subjective operational reliability assessment of maritime transportation system

被引:45
作者
Gaonkar, Rajesh S. Prabhu [1 ]
Xie, Min [1 ]
Ng, Mien Ming [1 ]
Habibullah, Mohamed Salahuddin [2 ]
机构
[1] Natl Univ Singapore, Dept Ind & Syst Engn, E1A,Engn Dr 2, Singapore 117576, Singapore
[2] Inst High Performance Comp, Singapore 138632, Singapore
关键词
Operational reliability; Maritime transportation system; Fuzzy sets; Fuzzy logic; EXPERT-SYSTEM; SAFETY; NETWORK; MARINE;
D O I
10.1016/j.eswa.2011.04.187
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
System reliability assessment is one of the major acts in the operation and maintenance of every industrial and service sector, which also holds true for maritime transportation system. The complexity of the maritime transportation system is a prime obstacle in the evaluation of the operational reliability of the system; mainly due to the fact that statistical data on the important parameters and variables is scarce. This makes the application of fuzzy sets and fuzzy logic a viable option to overcome the data problem with regards to imprecision or vagueness in parameters and variables values. In this paper, the different decisive factors, affecting maritime transportation systems, are modeled in the form of linguistic variables. Techniques such as aggregation, mapping of fuzzy sets using distance measure and fuzzy logic rule base are used to arrive at subjective operational reliability value. The complete procedure is demonstrated with an example. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:13835 / 13846
页数:12
相关论文
共 30 条
[1]  
Alexopoulos A.B., 2006, OPER RES INT J, V6, P55, DOI [10.1007/BF02941138, DOI 10.1007/BF02941138]
[2]  
[Anonymous], 2004, INT J RELIAB QUAL SA, DOI DOI 10.1142/S0218539304001592
[3]   MAritime RISk Assessment (MARISA), a fuzzy approach to define an individual ship risk factor [J].
Balmat, Jean-Francois ;
Lafont, Frederic ;
Maifret, Robert ;
Pessel, Nathalie .
OCEAN ENGINEERING, 2009, 36 (15-16) :1278-1286
[4]  
Bojadziev G., 2007, Fuzzy Logic for Business, Finance, and Management Modeling, V2nd
[5]  
Buckley J.J., 2002, INTRO FUZZY LOGIC FU
[6]  
Cai K., 1996, INTRO FUZZY RELIABIL
[7]   An expert system towards solving ship auxiliary machinery troubleshooting: SHIPAMTSOLVER [J].
Cebi, Selcuk ;
Celik, Metin ;
Kahraman, Cengiz ;
Er, I. Deha .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) :7219-7227
[8]   A risk-based modelling approach to enhance shipping accident investigation [J].
Celik, Metin ;
Lavasani, Seyed Miri ;
Wang, Jin .
SAFETY SCIENCE, 2010, 48 (01) :18-27
[9]   Marine and offshore safety assessment by incorporative risk modeling in a fuzzy-Bayesian network of an induced mass assignment paradigm [J].
Eleye-Datubo, A. G. ;
Wall, A. ;
Wang, J. .
RISK ANALYSIS, 2008, 28 (01) :95-112
[10]  
Grabowski M., 2007, MARITIME POLICY MANA, V34, P405, DOI DOI 10.1080/03088830701585084