The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship i...The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.展开更多
In recent years, maritime transportation has played an important role in global economy development. As a result, ship traffic has become more congested. Moreover, ship navigation is susceptible to weather and environ...In recent years, maritime transportation has played an important role in global economy development. As a result, ship traffic has become more congested. Moreover, ship navigation is susceptible to weather and environmental conditions, and in some cases, it may become dangerous. Therefore, vessels are subjected to high-risk navigation conditions. To understand the latent risk of ship navigation, this study focused on the actual ship behavior. Thus, an analysis of ship behavior was carded out using historical ship navigation based on automatic identification system data. Consequently, a dynamic analysis of the speed and encounter situation was performed. One of the main results of this work was the understanding of the latent risk involved in ships navigating the Seto Inland Sea, which is one of the most congested routes in Japan. Moreover, the risk areas were obtained, and visualized using a geographical information system. The obtained results can be applied to ensure safe navigation and the development of a safe and efficient navigation model.展开更多
针对传统循环神经网络提取船舶轨迹序列特征能力不足,导致预测结果与实际轨迹之间的误差较大,影响船舶调度与航行安全的问题,将双向门控循环单元(Bidirectional Gated Recurrent Unit, Bi-GRU)神经网络应用到船舶轨迹预测中。利用Bi-GR...针对传统循环神经网络提取船舶轨迹序列特征能力不足,导致预测结果与实际轨迹之间的误差较大,影响船舶调度与航行安全的问题,将双向门控循环单元(Bidirectional Gated Recurrent Unit, Bi-GRU)神经网络应用到船舶轨迹预测中。利用Bi-GRU神经网络模型具有的前瞻特性以及大量船舶自动识别系统(Automatic Identification System, AIS)数据,提出基于Bi-GRU的船舶轨迹预测模型。结果表明,Bi-GRU的预测精度较门控循环单元(Gated Recurrent Unit, GRU)有明显提升,均方误差降低13.0%,均方根误差降低6.5%,平均绝对误差降低16.5%。研究成果可为提高船舶交通服务系统安全管理水平、判断船舶交通风险程度及智能船舶碰撞预警提供理论支撑。展开更多
文摘The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.
文摘In recent years, maritime transportation has played an important role in global economy development. As a result, ship traffic has become more congested. Moreover, ship navigation is susceptible to weather and environmental conditions, and in some cases, it may become dangerous. Therefore, vessels are subjected to high-risk navigation conditions. To understand the latent risk of ship navigation, this study focused on the actual ship behavior. Thus, an analysis of ship behavior was carded out using historical ship navigation based on automatic identification system data. Consequently, a dynamic analysis of the speed and encounter situation was performed. One of the main results of this work was the understanding of the latent risk involved in ships navigating the Seto Inland Sea, which is one of the most congested routes in Japan. Moreover, the risk areas were obtained, and visualized using a geographical information system. The obtained results can be applied to ensure safe navigation and the development of a safe and efficient navigation model.
