Collision accident accounts for the largest proportion among all types of maritime accidents, emergency decision-making is essential to reduce the consequence of such accidents. This paper proposes a novel Bayesian Network based emergency decision-making model for consequence reduction of individual ship-ship collision in the Yangtze River. The kernel of this method is to propose a three-layer decision-making framework, to develop the graphical structure for describing the accident process and to establish the conditional probability tables for the quantitative relationships. The merits of the proposed method include the intuitive representation of accident development, easy to implement, ability to deal with incomplete information and updated information. This proposed method is applied to a typical collision accident in the Yangtze River. Consequently, this paper provides a practical and novel decision-making method for collision accidents.

The water level fluctuations in the upper reach of dam reservoirs may result in increasing occurrence probabilities of ship grounding accidents, which is especially prominent in the Three Gorges Reservoir. Grounding accidents may not only cause congestion of the traffic but also lead to loss of properties and pollution to the maritime environment. An analytical model incorporating Bayesian Network is proposed to estimate the occurrence likelihood of a ship being grounded in the fluctuating backwater zone. The proposed model comprehensively considers the characteristics of the ship's properties, organizational factors, hydrological conditions and human factors from a systematic perspective. Historical data collected from the Chongqing Maritime Safety Administration, together with incident reports, are used to develop a quantitative model. The developed model in this paper concludes that out of twenty-six factors, the area of the fluctuating backwater zone, the month, and water level are the predominant factors for the occurrence of grounding accidents in the Three Gorges Reservoir. The results can be used by maritime stakeholders to take mitigation measures for grounding accident reduction.

Offshore wind farms have developed fast as an environmentally friendly source of energy. The submarine power cable of the offshore wind farm, used for connecting power generation devices to onshore equipment, may have a significant impact on navigation safety and is prone to being damaged (e.g. caused by fishing or emergency anchoring by ships) when adopting unfavorable routing. This paper proposes a fuzzy evidential reasoning method for submarine power cable routing selection of the offshore wind farm by comprehensively considering the conditions for cable laying and its influence on maritime safety. The kernel of this approach is to establish a three-layer decision-making framework after fuzzification of the input variables, to derive the belief rule base, and to obtain the optimal routing from the submarine power cable candidates using evidential reasoning and index value. The proposed approach is applied to a real routing selection problem of a submarine power cable for an offshore wind farm in Zhejiang Province of China. The resulting choice corresponds to the discussions in a workshop unanimously.