2,222 research outputs found

    Research on the collision risk of ships in Chengshanjiao Water based on SVM

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    Research on the benefit evaluation of ships’ routeing systems in Jiangsu Section of the Yangtze River

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    New Intelligent Method of Forecasting Control for Fishing Boat Security in the Coastal Area of Fujian

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    Abstract: To ensure the fishing boat security in the coastal area of Fujian, it is imperative to develop efficient forecasting control system to manage the boats operation in a safe and orderly process. The core issue of establishing the forecasting control system is to predict the relationship of the real time traffic flow and the boat security condition. However, literature review shows that limited reports have addressed on this problem. Hence, a new intelligent forecasting control method base on the Chaos-Particle Swarm Optimization (PSO) and Fuzzy Neural Network (FNN) is proposed for the short time traffic flow prediction in this paper. The Empirical Mode Decomposition (EMD) was first used to denoise the original ship traffic flow observation and then the Chaos-PSO-FNN was applied to the forecasting of the ship traffic flow and hence established the relationship of the real time traffic flow and the boat security condition. The advantage of the proposed approach is that the Chaos-PSO is employed to optimize the FNN parameters to overcome the premature problem of the FNN. As a result, the forecasting control performance is enhanced greatly. In the experiment analysis, the fishing boat traffic information provided by the Fujian marine bureau has been used to evaluate the newly proposed method. The analysis results demonstrate that the proposed Chaos-PSO-FNN method can extract distinct features of the traffic data and the prediction rate is beyond 93.7%. In addition, it found that the fishing boats is supposed to be safe when their travel time avoids the rush time of the traffic flow. This result agrees well with the real data. Thus, the new intelligent forecasting control method for fishing boat security can be used in practice

    Safety assessment of navigational environment in Dalian Beiliang Port

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    Prediction of Emergency Preparedness Level On-Board Ships Using Discrete Event Simulation: the Case of Firefighting Drill

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    This paper proposes a hybrid approach, including Fuzzy Dematel (FD) integrated with Discrete Event Simulation (DES), to predict emergency preparedness levels on-board ships. The FD used critical factors that affect emergency preparedness to conduct a DES based on real firefighting drill records collected from 45 merchant ships. The simulation results showed the average duration of on-board drills in ideal conditions (27.47 min.), in the worst-case scenario (51.49 min.), for Ship A (29.99 min.), and Ship B (28.12 min.). Based on the findings, recovery actions linked to the factors have been recommended to promote on-board implementation. The proposed model is of great importance to shore-based managers, allowing them to monitor the emergency preparedness level of the fleet continuously, even during pandemics. Further studies are planned to develop a remote monitoring system that would digitalize the existing response procedures in emergency situations

    Quantifying Systemic Risk

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    Anticipating the Effects of Economic Displacement in Marine Space with Agent Based Models

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    As marine space is managed into appropriate resource use areas, it is inevitable that some is allocated towards a mutually exclusive spatial activity. This exclusion results in displacement that has real economic consequences. When a wind energy area is placed in coastal waters, navigable space is reduced and vessels are displaced from their former routes. The USCG is concerned that re-routing will result in vessels navigating within closer proximity than they would otherwise in an open ocean scenario, and fear that this will increase the risk of vessel collision (USCG 2016). They recommend research into tools that are capable of predicting changes in vessel traffic patterns (USCG 2016). Agent based models are a method capable of predicting these traffic patterns, and are composed individual, autonomous goal directed software objects that form emergent behavior of interest. Agents are controlled by a simple behavioral rule, they must arrive at their destination without colliding with an obstacle or other vessel. They enforce this rule with the gravitational potential that exists between two objects. Attractive forces pull each agent towards their destination, while repulsive forces push them away from danger. We validated simulated vessel tracks against real turning circle test data, tested for the presence of chaotic systems, developed metrics to assess transportation costs, and applied the method to assess a wind energy area located outside of the entrance to the Port of New York and New Jersey

    Chinese vessel pollution prevention in the era of the green economy

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