中国舰船研究2017，Vol.12Issue(5)：97-103,7.DOI:10.3969/j.issn.1673-3185.2017.05.012
基于神经网络和遗传算法的系泊优化设计
Mooring optimization design based on neural network and genetic algorithm
摘要
Abstract
[Objectives]In order to maintain the stability of the position of a ship, a mooring system is required to reduce the translational motion of floating structures.[Methods]Taking a pipe-laying vessel in the South China Sea as an example, it is possible to minimize the translational displacement of the anchor chain in the mooring state by optimizing the arrangement of the anchor line to ensure the safe operation of the ship. First, we can obtain several different layouts through orthogonal testing after selecting the azimuth and distance of the anchor chain as the test factors. We then calculate the different movements and force in time domain value at different wave direction angles for each layout using Moses. With the calculation results as samples, the BP neural network method achieves time domain simulation in Moses. After choosing the azimuth and distance of the anchor chain as the optimization variables, and with each wave-weighted translational displacement probability as the optimization objective, we find that the generalization capability of the BP neural network method can replace the time domain calculation of Moses.[Results]Using a genetic algorithm optimization solution, movement is significantly reduced at different wave direction angles.[Conclusions]This conclusion can provide a reference for the mooring arrangements of floating structures.关键词
系泊优化/BP神经网络/遗传算法/Moses/时域分析Key words
mooring optimization/BP neural network/genetic algorithm/Moses/time domain analysis分类
交通工程引用本文复制引用
许小颖,周盼,王宽..基于神经网络和遗传算法的系泊优化设计[J].中国舰船研究,2017,12(5):97-103,7.基金项目
文华学院青年基金资助项目(J02e0540211) （J02e0540211）
