摘要
传统的旅游高峰期船舶海上交通规划方法的最小航时规划结果与设定要求不符,为了解决这一问题,提出基于神经网络的旅游高峰期船舶海上交通规划研究。运用神经网络算法优化处理船舶海上交通航迹,在此基础上,设计船舶海上交通规划方案,先确定阶段变量,再选择状态变量,实现旅游高峰期船舶海上交通规划。由此完成基于神经网络的旅游高峰期船舶海上交通规划研究。最后,进入实验部分,对比2种方法的最小航时规划结果是否符合设计要求,实验结果表明,传统的旅游高峰期船舶海上交通规划方法的有效波高小于3.5 m,与约定波高5 m要求不符。而使用所提方法的有效波高大于5 m,与约定波高5 m要求相符。
In order to solve this problem, the paper puts forward the research of marine traffic planning based on neural network. On the basis of the neural network algorithm to optimize the ship’s sea traffic path, the paper designs the plan of ship’s sea traffic planning, first determines the stage variables, then selects the state variables, and realizes the plan of ship’s sea traffic during the peak period of tourism. Thus, the research of marine traffic planning based on neural network is completed. Finally, enter the experimental part, compare the results of the two methods to see whether they meet the design requirements. The experimental results show that the effective wave height of the traditional maritime traffic planning method is less than 3.5 m, which is not in line with the requirements of the agreed wave height of 5 m. The effective wave height of the proposed method is greater than 5 m, which is in line with the requirements of the agreed wave height of 5 m.
作者
赵亮
ZHAO Liang(Xinjiang Vocational and Technical College of Communications,Urumqi 831401,China)
出处
《舰船科学技术》
北大核心
2020年第2期73-75,共3页
Ship Science and Technology
基金
2018年交通行指委第一批交通运输职业教育科研立项项目(2018YJ104)
关键词
神经网络
旅游高峰期
船舶
海上交通
规划航迹
能量消耗
neural network
tourism peak
ship
maritime traffic
planning route
energy consumption
作者简介
赵亮(1981-),男,工程硕士,讲师,研究方向为物流管理及海事管理。
