Web application with data centric approach to ship powering prediction using deep learning

• Main Authors: Khairuddin, Jauhari, Abdul Malik, Adi Maimun, Hiekata, Kazuo, Siow, Chee Loon, Ali, Arifah
• Format: Article
• Language: English
• Published: Elsevier B.V. 2022
• Subjects: Q Science (General); QA Mathematics; TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://eprints.utm.my/104129/1/AdiMaimunAbdul2022_WebApplicationwithDataCentricApproach.pdf; http://eprints.utm.my/104129/; http://dx.doi.org/10.1016/j.simpa.2022.100226
• Institution: Universiti Teknologi Malaysia

This work describes an AI-based web application to predict passenger ship powering requirements. The data centric approach is developed based on the actual passenger ship design data as a design tool to assist naval architects to quickly estimate the ship brake power. It emphasised on the preliminar...