摘要
针对数据挖掘技术在散货船代数据中的应用,通过聚类规则分析航线繁忙度和航线价值。首先预处理原始散货船代数据并提取符合挖掘目标的数据;再通过改进的k-means算法挖掘预处理后的数据;最后对挖掘结果进行分析,为船代企业的资源分配及策略制定提供参考。
Aiming at the application of data mining technology on bulk shipping agency data, analyses lane busy degree and lane value based on cluster rules. Firstly, the original bulk shipping agency data is preprocessed to get the data agreed with the goal of mining task. And the preprocessed data is mined by the improved k-means algorithm, finally analyses mining resuit, which provides the reference for allocating the resource of shipping agency and making the tactics.
出处
《现代计算机》
2008年第4期32-35,共4页
Modern Computer
