Vessel Collision Causation Analysis Based On Apriori Algorithm

In marine traffic safety,the key point of the relevant department management is to prevent and reduce the number of marine traffic accidents.Meanwhile,it is also one of the important research subjects of experts and scholars at home and abroad.Marine traffic accident statistics show that collision accidents have been in the forefront of all kinds of accidents at sea.There are many factors which can lead to a collision,but studies confirm more than 80%of the collision accidents that relate to human factors.Finding the cause of ship collision accidents has become the focus of the study.The thesis first analyzed the process of collision,and then integrated the various national maritime survey statistical model of human error and related research.On this basis,through reading a large number of ship collision accident investigation reports,the thesis confirmed the types of human error that leads to ship collision accident and used the Apriori algorithm in data mining technology to human error and influencing factors.Then it can find out the influence of frequent items,to determine the maximum impact factors of human error.Finally,making use of bayesian network structure and the accident cause chain analysis of human error can obtain the formation process of ship collision accidents.Combining Apriori algorithm for mining frequent human error combination and reasoning about the accident cause of causal chain can be concluded what the most likely accident cause chain is.If we can cut off any error in the chain link,we can effectively reduce the incidence of accidents.The study of ship collision avoidance provides a new idea and new method.’In this thesis,the research on management of ship collision accident prevention has certain guiding significance,at the same time,the method for other types of marine traffic accident cause analysis has certain reference significance.