SNS-MEBN Based Method for Situational Awareness of Ship Navigation

Situational Awareness of Ship Navigation plays an important role in the safety and security of waterway transport. However, the current ship navigation safety assessment method cannot effectively express the uncertain knowledge. In this paper we propose a method for Ship Navigation Safety based on Multi-Entity Bayesian Networks (SNS-MEBN) in order to evaluate the ship navigation safety. This could reduce the factors of ship navigation safety based on Rough Set Condition Information Entropy (RSCIE). SNS-MEBN is constructed by combining Multi-Entity Bayesian Networks (MEBN) with the reduction result, thus the expression of uncertain knowledge in the process of ship navigation safety assessment is realized. Inference of ship navigation safety is made by combining SNS-MEBN and Bayesian Network Joint Tree Reasoning (BNJTR) algorithms. Finally, to validate the proposed method, experiments are conducted over the navigation data of ships navigating from Hejiangmen to Wangyemiao, collected by the Changjiang Waterway Bureau were validated. The experimental results showed that proposed method has the better accuracy.