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Clustering Algorithm for a Set of Machine Parts on the Basis of Engineering Drawings

机译:基于工程图纸的一组机器零件聚类算法

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摘要

For industrial logistics tasks, an algorithm for clustering a given set of machine parts on the basis of engineering drawings is proposed. To speed up clustering, the values of each parameter are fuzzified and local maximums of the N-dimensional histogram are sought. The search uses the selection of adjacent vectors based on the recalculation of coordinates from the N-dimensional space to a one-dimensional space and vice versa and on the comparison with coordinates of neighboring vectors. Thereby the algorithm finds the cluster vertices in a single pass, and it does not require the creation of numerous local lists or vector adjacency graphs, which improves the efficiency of the clustering algorithm. Experimental results on automatic grouping of machine parts on the basis of drawings are discussed.
机译:对于工业物流任务,提出了一种基于工程图形集群聚类一组机器零件的算法。为了加速群集,每个参数的值是模糊的,并寻求N维直方图的局部最大值。该搜索基于从N维空间的坐标重新计算到一维空间的坐标并反之亦然以及与相邻向量的坐标的比较来选择相邻矢量的选择。因此,算法在单个通行证中找到群集顶点,并且它不需要创建众多本地列表或矢量邻接图,这提高了聚类算法的效率。讨论了在图纸基础上自动分组机械部件的实验结果。

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