摘要
海上气象灾害是影响船舶航行最危险的环境因素,如何通过船用气象传感网络采集的数据进行气象灾害预测及决策是现代海上决策系统研究的重点。随着计算科学的发展,数据挖掘在大数据处理中得到广泛应用,根据船用气象数据的噪声及边界模糊特性,本文选择基于二型模糊数据挖掘的船用气象数据决策模型,对气象数据采用密度因子进行分布调节,同时将多维气象数据进行降维处理,设计高效的海上气象灾害决策系统,最后进行实验。
Marine meteorological disasters are the most dangerous environmental factors that affect the navigation of the ship. How to forecast and make the meteorological disasters through the data collected by the marine meteorological sensor network is the key point of the modern maritime decision system. With the development of computational science,data mining has been widely used in large data processing. According to the noise of the marine meteorological data and the fuzzy characteristics of the boundary, this paper selects the decision model of the marine meteorological data based on two fuzzy data mining, at the same time, the multi dimension meteorological data is reduced to deal with the dimension, and an efficient decision-making system is designed.
出处
《舰船科学技术》
北大核心
2017年第5X期164-166,共3页
Ship Science and Technology
关键词
模糊聚类
数据挖掘
气象灾害
fuzzy clustering
data mining
meteorological disaster
