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

• Main Authors: Yang Ou, Zheng Jiang Liu, Hamid Reza Karimi, Ying Tian
• Format: Article
• Language: English
• Published: Hindawi Limited 2014-01-01
• Series: Abstract and Applied Analysis
• Online Access: http://dx.doi.org/10.1155/2014/278694

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.