Author(s): L.P. Perera, B. Mo
Journal/conference: IEEE Transactions on Vehicular Technology
Date: 06.06.2017

Machine Learning based Data Handling Framework for Ship Energy Efficiency

Study by L.P. Perera and B. Mo published in IEEE Transactions on Vehicular Technology.

This study proposes a machine intelligence (MI) based data handling framework for ship performance and navigation data to improve the quality of the respective navigation strategies. The proposed framework is divided into two main sections of pre and post processing. The data pre-processing is an onboard application that consists of sensor faults detection, data classification and data compression steps. The data post processing is a shore-based application (i.e. in data centers) and that consists of data expansion, integrity verification and data regression steps. Finally, a ship performance and navigation data set of a selected vessel is analyzed through the proposed framework and successful results are presented in this study.


SP4 Performance in a Seaway; WP4 Ship system integration and validation