Open AccessResearch on Ship Route Planning Method Based on Neural Network Wave Data Forecast
Author(s) -
Jin Xin,
Junting Xiong,
Dongliang Gu,
Chengtao Yi,
Yingjie Jiang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/638/1/012033
Subject(s) - computer science , plan (archaeology) , artificial neural network , graphics , port (circuit theory) , set (abstract data type) , route planning , operations research , reading (process) , data set , data mining , network planning and design , artificial intelligence , engineering , transport engineering , computer graphics (images) , telecommunications , archaeology , law , political science , electrical engineering , history , programming language
Route design is an indispensable skill for ships and navigators. However, in actual work, most of the current route design still lies in manually reading port information and other graphic materials, and then revising the sailing plan in conjunction with the weather forecast. On the one hand, this method is not accurate enough, and the graphics and text data are not sufficiently real-time. On the other hand, this method has the disadvantages of being cumbersome and labor-intensive. In response to the above problems, this article combines the actual data set of ICOAD, applies the neural network model, and uses the A* algorithm to plan the route, which provides a reference for the application of artificial intelligence to ship route planning.