An Investigation into the Operational Characteristics of High-Speed Crew Boat Based on Artificial Neural Network

• Published in: IOP conference series. Earth and environmental science 2020-08, Vol.557 (1), p.12054
• Main Authors: Riyadi, S, Utama, I K A P, Aryawan, W D, Rulaningtyas, R, Thomas, G A
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Back propagation networks; Boats; High speed; Maneuvers; Mathematical models; Neural networks; Optimization; Statistical analysis; Statistical models
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/557/1/012054

Estimating shaft power of a crew boat is very important to be analysed because it has high-speed operational characteristics along with limited routes. To understand the phenomena, 3 sister crew-boats with operational distance about 40-60 nautical miles every day are investigated. The daily operational time is 8 hours and the configurations are: 4.04% full speed, 13.63% economical speed, 1.81% slow speed, 7.65% snatching, 1.25% manoeuvring, 5.29% idle, and the remaining time is in standby condition. The crew boats are fitted with a monitoring system namely SHIMOS®, in which data is sent to a server in the centre office every 2 minutes. The data consists of time capture, boat position (latitude and longitude), speed, left and right RPM engine, left and right flow-meter data engine, and average of fuel consumption data in everyday operation. Three years of data has been collected for the vessel. The present study proposed characteristics of crew-boat shaft power, which affected by external factors using Artificial Neural Network (ANN) back propagation method and optimisation in 4 hidden layers and 40 neurons with relative error 6.2%. The results demonstrates good agreement with previous popular method that using statistical models.