数据挖掘聚类算法在船岸一体化平台中的应用

Application of Clustering Algorithm for Data Mining in Ship-Shore Integration Platform

船舶的远程动态跟踪及数据采集、处理与应用是船岸一体化平台的一项主要内容。船岸一体化平台收集的数据呈现复杂的关系,而利用数据挖掘技术能从中发现知识或规律,及时分析以提供决策支持。介绍船岸一体化平台的数据采集过程、对数据的要求以及数据挖掘方法的相关理论。以船舶节能为研究目标,举例说明k均值聚类算法的应用过程,为船岸一体化平台的数据处理与功能实现提供一个新的思路。

Ship-shore integration platform performs ship tracking,data acquisition and processing,and management services.The large amount of data collected in ship-shore integration platform shows a complex relationship and the data mining technique is necessary for extracting knowledge and discovering laws from data and timely supporting decision making.The data acquisition process of the platforms and their requirements for the information as well as some concepts of data mining are introduced.The practical application of k means clustering algorithm aiming for energy saving is illustrated.This study demonstrates a new approach of developing a ship-shore integration platform.