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AIS Data-based Decision Model for Navigation Risk in Sea Areas

Published online by Cambridge University Press:  07 November 2017

Lianbo Li ,
Wenyu Lu ,
Jiawei Niu ,
Junpo Liu  and
Dexin Liu
Lianbo Li*
Affiliation:
(Navigation College, Dalian Maritime University, Dalian 116026, China)
Wenyu Lu
Affiliation:
(School of Foreign Languages, Dalian Maritime University, Dalian 116026, China)
Jiawei Niu
Affiliation:
(Navigation College, Dalian Maritime University, Dalian 116026, China)
Junpo Liu
Affiliation:
(Navigation College, Dalian Maritime University, Dalian 116026, China)
Dexin Liu
Affiliation:
(Navigation College, Dalian Maritime University, Dalian 116026, China)
*
(E-mail: lilianbodlmu@163.com)
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Abstract

The safety of maritime transportation has become increasingly important in recent decades. In this paper, a decision model (a multi-objective and multi-layer fuzzy optimisation model) for navigation risk in different sea areas is established. This is done according to the evaluation index system based on relative data extracted and analysed from Automatic Identification Systems (AIS) information and the multi-objective and multi-layer fuzzy optimisation theory. Then, sorted by an optimal relative membership degree vector and calculated from lower layer to higher layer, the sea areas which have higher navigation risk are selected. Finally, the decision model is shown to be scientific and practical since the results from it are basically consistent with real traffic in Chengshantou waters and the results from the fuzzy comprehensive evaluation model. With the decision model, navigation risk judgments in different sea areas can be offered. It can also provide decision making references to the design of ship routing systems, the layout of search and rescue sites, the configuration of rescue forces and the administration of navigation safety.

Keywords

Automatic Identification System information (AIS information)Navigation riskEvaluation index systemMulti-objective and multi-layer fuzzy optimisation theory
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 3 , May 2018 , pp. 664 - 678
Copyright
Copyright © The Royal Institute of Navigation 2017 

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