Open AccessResearch on adaptive ship trim energy saving scheme based on intelligent loading
Author(s) -
Yibo Gao
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/634/1/012015
Subject(s) - trim , particle swarm optimization , range (aeronautics) , trimming , computer science , energy (signal processing) , process (computing) , scheme (mathematics) , set (abstract data type) , algorithm , deep learning , artificial intelligence , real time computing , control theory (sociology) , simulation , engineering , control (management) , mathematics , aerospace engineering , mathematical analysis , statistics , programming language , operating system
The system is a set of control system based on ship trimming energy-saving designed through deep learning algorithm, particle swarm algorithm and data optimization. Through the deep learning algorithm, the collected data is deep learning, the result of intelligent learning is used as the objective function, and the particle swarm algorithm combined with the loading software is used to adjust the loading state, sail with a fixed inclination angle and collect this fixed inclination angle during the voyage. A certain range of nearby data is systematically revised to make the system more perfect. Finally, a universal method can be obtained, which can be applied to different types of ships, and the corresponding trim optimization suggestions will be given to the complicated factors encountered in the navigation process.