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Prediction of ship's speed through ground using the previous voyage's drift speed

Yamane D., Kano T.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2023

Vol. 17 No. 1

129--137

In recent years, 'weather routing' has been attracting increasing attention as a means of reducing costs and environmental impact. In order to achieve high-quality weather routing, it is important to accurately predict the ship's speed through ground during a voyage from ship control variables and predicted data on weather and sea conditions. Because sea condition forecasts are difficult to produce in-house, external data is often used, but there is a problem that the accuracy of sea condition forecasts is not sufficient and it is impossible to improve the accuracy of the forecasts because the data is external. In this study, we propose a machine learning method for predicting speed through ground by considering the actual values of the previous voyage’s drift speed for ships that regularly operate on the same route, such as ferries. Experimental results showed that this method improves the prediction performance of ship’s speed through ground.

Eco-shipping project with a speed planning system for Japanese coastal vessels

Sato K., Kano T.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

2016

nr 46 (118)

147++154

The Eco-Shipping Project has conducted demonstrative experiments since the beginning of this year using about 40 vessels including coastal cement carriers, oil tankers, and ro-ro ships supported by the Ministry of the Environment. The goal of this project is to reduce fuel and CO₂ emission by 15%. The authors developed a voyage speed planning system which calculates a vessel optimum speed plan that takes into account weather forecast information and generates minimized fuel consumption for an operation. This paper describes an approach to optimize speed profiles on ship just-in-time voyages to save fuel and reduce CO₂ emissions, and introduces some cases of experimental results.