# Machine Learning Approaches for Ship Speed Prediction towards Energy Efficient Shipping
## 2 Material and Methodology
### Data Acquisition  
A 2018 AIS satellite data and noon-report weather data of 14 tanker and 62 cargo ships were collected. The AIS data and noon-report marine weather data was provided by Lab021, and the AIS data collected within an average of 3 min time intervals. The resolution of the weather data is 0.5 degrees in the latitude and longitude directions. In this study, the proposed framework was validated by using five datasets with different types of routes and ships among the total data. The description of both the AIS and weather data is shown in Table 1. The AIS data consist of static information, dynamic information, and navigation information. Static information includes the identification numbers of the ship such as its Maritime Mobile Service Identity (MMSI) and International Maritime Organization (IMO) number, call sign and name, ship's types and dimensions (dimension A-D), and location of the electronic fixing device antenna. Since static information is rarely changed, the data are manually updated. Dynamic data include operational information related to the navigation of a ship. The data are collected with some time interval (data time stamp) and automatically updated according to the navigational status of the ship. Similarly, weather data considerably affect ship speed, such that it must include main features to predict the performance of a ship (SOG). For example, as the hull of a vessel goes to the sea, it highly induces resistance when it is sailing due to friction and wave-making [15]. F \begin{table}
\begin{tabular}{p{14.2 pt} p{14.2 pt} p{14.2 pt} p{14.2 pt} p{14.2 pt} p{14.2 pt}} \hline \hline
**No** & **Parameter** & **Unit** & **Remark** & **No** & **Parameter** & **Unit** & **Remark** \\ \hline
1 & MMSI & – & 24 & Total wave height & m \\ \hline
2 & MO number & – & 25 & Total wave direction & deg. \\ \hline
3 & Call sign & – & 26 & Total wave period & sec \\ \hline
4 & Name & – & 27 & Wind wave height & m \\ \hline
5 & Type of ship & – & AIS data for static info (Msg. type 5) & 28 & Wind wave direction & deg. \\ \hline
6–9 & Dimension A-D & m & 29 & Wind wave period & sec \\ \hline
10 & Electronic fixing device & – & 30 & Swell wave height & m \\ \hline
11 & ETA & sec & 31 & Swell wave direction & deg. \\ \hline
12 & Max straight & m & 32 & Swell wave period & sec \\ \hline
13 & Mg type & – & 33 & Wind UV & m/s \\ \hline
14 & Date time stamp & KST & 34 & Wind VV & m/s \\ \hline
15 & MMSI & – & 35 & Mean sea pressure level & hPa \\ \hline
16 & Latitude & DMS & 36 & Pressure surface & hPa \\ \hline
17 & Longitude & DMS & 37 & Ambient temperature & °C \\ \hline
18 & SOG & knot & AIS data for dynamic info (Msg. type 123) & 38 & Sea surface salinity & Psu \\ \hline
19 & ROT & deg/min & dynamic info (Msg. type 123) & 39 & Sea surface temperature & °C \\ \hline
20 & COG & deg. & 40 & Current UV & m/s \\ \hline
21 & True heading & deg. & 41 & Current VV & m/s \\ \hline
22 & Navigational status & – & & & \\ \hline
23 & Mg type & – & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters of the automatic identification system (AIS) and weather data. Figure 1: Scheme of the suggested methodology. occurs at the drawn part of the body, and thus, the loading condition of the ship and the roughness of the hull have an effect on the hull resistance of a vessel. Waves also cause additional resistance due to the pitch and heave motions of the vessel and the reflection of the short waves on the hull [16]. Since wave resistance is continually varying over time and will be added to the total resistance obtained at each specific location, it must be considered when predicting the performance of a ship over its voyage. The total resistance of a vessel also depends on the properties of the water and is directly proportional to the viscosity and density of the seawater [15]. A higher viscosity or a higher density of the water will increase the resistance of the vessel.