Automatic Identification System (AIS) based Ship Heading Prediction using Artificial Neural Network and Wide Genetic Algorithm

International Maritime Organization (IMO) requires ship with more than 300 gross tonnages to have Automatic Identification System (AIS) onboard. AIS is used as a navigational aid to ensure the safety of ship operation including collision avoidance, vessel tracking, and accident investigation. AIS Transponder is installed onboard ship and transmitted data will be received by the base station as AIS data receiver. AIS Transponder provides information for instance a unique identification, position, course, and speed. Then those data will be utilized for many applications. Ship’s movement information obtained from AIS such as position and heading can be utilized as an early warning to avoid the event of the collision. In some cases, ship heading data is unidentified caused by transponder incompatibility and mistakenly conducting setup of AIS transponder. To solve the problem, extrapolation method can be used to predict the ship’s heading. However, this method has the disadvantage since it only considers the location of ships while the distinctive area near the port is ignored. This paper aims to develop a method to predict the ship heading based on AIS historical data of ship’s movement using Artificial Intelligence (AI). Artificial Neural Network (ANN) has been chosen as AI prediction model. There are two pre-processing should do before training process such a down sampling and sliding window. Wide Genetic Algorithm (WGA) is used for ANN training process to create ANN model. WGA-ANN computes the ship heading by predicting the next geolocation of ship.