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

Yang Ou,Ying Tian,Hamid Reza Karimi,Zheng Jiang Liu

doi:10.1155/2014/278694

Abstract

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.

Highlights

With the development of shipping science, improvement of vessel technology, and the rising trend of multinational manning of ships, maritime safety and marine pollution prevention have been the hot spots in study of the maritime field by all the countries
The ratio of cross level weight is counted by asking the maritime investigation officer who takes part in the investigation of the accident directly or calling to the crew in the accident report
The items of bridge resource management (BRM) are considered as attributes of the algorithm, and the ten surface reasons coming from the database are as the basic attributes which have certain contributions to the attributes

Summary

Introduction

With the development of shipping science, improvement of vessel technology, and the rising trend of multinational manning of ships, maritime safety and marine pollution prevention have been the hot spots in study of the maritime field by all the countries. Against this background, the focuses of maritime safety research are mainly on two aspects. The good seamanship and the excellent teamwork in the deck crew management of the ship are both the most important factors to avoid the vessel accidents. A few literatures focus on the data analysis between the vessel accidents and items of BRM. It is necessary to find some associations, which can reflect the deep inducements of accidents, from the collected maritime accident data to guide the seafarer training

Objectives

Results

Conclusion