摘要
阐述船舶智能辅助避碰系统的基本决策过程,聚类算法在危险区域划分中的应用,以及在碰撞危险度计算中利用大量实船数据训练神经网络模型的机器学习方法。优化相关参数的计算方法,提升智能辅助避碰系统的可靠度和实用性。
The basic decision-making process of the ship intelligent assisted anti-collision system,the application of clustering algorithm to the division of dangerous areas and the method of using large amount of real ship data to train the neural network model in the calculation of collision risk was stated.The calculation methods of the relevant parameters were optimized,and the reliability and practicability of the ship intelligent assisted anti-collision system were improved.
作者
杨凌波
YANG Lingbo(Beijing Highlander Digital Technology Co.,Ltd.Beijing 100095,China)
出处
《船舶设计通讯》
2019年第2期79-82,共4页
Journal of Ship Design
基金
智能船舶1.0研发专项——船舶辅助自动驾驶系统开发。
关键词
机器学习
避碰
智能船
智能决策
宽水域
machine learning
anti-collision
intelligent ship
intelligent decision
open sea area