Abstract
As interest in the design of eco-friendly and smart ships has been widely increased worldwide, there is a demand for the development of element technologies. Among them, a representative one is a technology for the economical route planning of ships. When finding the economical route for ships, it is essential to estimate the fuel consumption of the ships. For the estimation, the ocean weather should be predicted in advance. In general, ocean weather can be obtained from overseas weather centers. In this study, a prototype program was developed using a prediction model for the ocean weather based on deep learning, which had been developed in the previous study of the authors. For its implementation, MarineWiz, which is a software development kit (SDK) for Korean shipbuilding industries, was used. The developed program consists of a prediction library for the ocean weather and a visualization library. To check the applicability of the developed program, it was applied to the route planning of a 13,000 TEU-class container ship.
