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Abstract and Applied Analysis
Volume 2014, Article ID 278694, 8 pages
Research Article

Multilevel Association Rule Mining for Bridge Resource Management Based on Immune Genetic Algorithm

1College of Navigation, Dalian Maritime University, Dalian 116026, China
2Department of Engineering, Faculty of Engineering and Science, The University of Agder, 4898 Grimstad, Norway
3College of Engineering, Bohai University, Jinzhou 121000, China

Received 31 December 2013; Revised 22 January 2014; Accepted 22 January 2014; Published 27 February 2014

Academic Editor: Shen Yin

Copyright © 2014 Yang Ou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper is concerned with the problem of multilevel association rule mining for bridge resource management (BRM) which is announced by IMO in 2010. The goal of this paper is to mine the association rules among the items of BRM and the vessel accidents. However, due to the indirect data that can be collected, which seems useless for the analysis of the relationship between items of BIM and the accidents, the cross level association rules need to be studied, which builds the relation between the indirect data and items of BRM. In this paper, firstly, a cross level coding scheme for mining the multilevel association rules is proposed. Secondly, we execute the immune genetic algorithm with the coding scheme for analyzing BRM. Thirdly, based on the basic maritime investigation reports, some important association rules of the items of BRM are mined and studied. Finally, according to the results of the analysis, we provide the suggestions for the work of seafarer training, assessment, and management.