|
|
Publications
Yu, Q., Teixeira, A.P., Liu, K., Rong, H. and Guedes Soares, C. (2021), “An integrated dynamic ship risk model based on Bayesian Networks and Evidential Reasoning”, Reliability Engineering and System Safety, Vol. 216, 107993.
This paper proposes a probabilistic framework for assessing the navigational risk of individual ships and of the maritime traffic based on a hybrid approach and multiple data sources. A Bayes-based network learning approach uses data from the New Inspection Regime of the Paris MoU on Port State Control to train the interrelationships among parameters and uses these parameters to evaluate ship static risks. Other data sources are used to develop a Bayesian Network model to assess the navigational risk of the ship. The data is aggregated by Bayesian Network and Evidential Reasoning approaches to evaluate the overall risk of the ships in coastal waters. The objective of the study is to develop a model to assess the risk of the ship considering its static risk profile and geographical-dependant risk factors related to the characteristics of the traffic flow and other local characteristics that influence the navigational risk of the ship. The results show that the integrated approach is able to assess the risk based on multiple data sources and to identify the most critical circumstances and the key impact factors of the navigational risk of the ships, providing empirical evidence of using multiple data sources in risk analysis applications.
If you did not manage to obtain a copy of this paper: Request a copy of this article
For information about all CENTEC publications you can download: Download the Complete List of CENTEC Publications
|