Finally the hierarchical agglomerative clustering algorithm is applied to the existing laboratory equipment, remote sensing images (infrared imaging system, multi-spectral camera, UV cameras) to obtain the 5-band image.
最后把分层合并聚类算法应用于实验室已有的遥感设备(红外热像仪、多光谱相机、紫外相机)获取的5波段多光谱溢油图像。
参考来源 - 高光谱溢油图像波段选择在油膜厚度估算中的应用·2,447,543篇论文数据，部分数据来源于NoteExpress
为了构建聚类代表，算法通过构造最佳匹配树，合并树，修剪树三步来实现。
The cluster representative was constructed by three successive steps named Tree matching, Tree merging and Tree pruning.
合并连接紧密度高的结点，得到最后的聚类结果。
Combining the nodes which have the high joint degree, we can get the result of the clustering.
然后是用F—统计量法对物流节点类型确定的聚类结果进行校验，分析其聚类效果是否满意，合并是否合理。
Thirdly, use F-test to analyze whether the results got by the method forward used are satisfactory and reasonable or not.
应用推荐