Ship Mooring Optimization Based on Genetic Algorithm and BP Neural Network

DOI

10.2991/isaeece-17.2017.38How to use a DOI?

Keywords

Mooring optimization; Moses; Time domain; BP neural network; Genetic algorithm

Abstract

According to a pipe laying vessel in the South China Sea, we can get different mooring layouts with anchor distance and angle as factors of the orthogonal test. Then the stress and motion displacement of anchor based on different layouts are calculated by using Moses software in different wave direction. The above results are taken as samples, and the BP neural network is trained to replace the Moses time domain calculation. Take the anchor distance and angle as the optimization variable and the weighted translational displacement of different wave direction as optimization objective. Finally, by using genetic algorithm the translational displacement of the vessel at each wave direction significantly reduced. The optimization effect is obvious, and it provides a reference for the mooring arrangement of offshore floating structures.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Xiaoying Xu
AU  - Kuan Wang
PY  - 2017/03
DA  - 2017/03
TI  - Ship Mooring Optimization Based on Genetic Algorithm and BP Neural Network
BT  - Proceedings of the 2017 2nd International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2017)
PB  - Atlantis Press
SP  - 205
EP  - 210
SN  - 2352-5401
UR  - https://doi.org/10.2991/isaeece-17.2017.38
DO  - 10.2991/isaeece-17.2017.38
ID  - Xu2017/03
ER  -