in condition monitoring. The identification of operation profiles during production is therefore important. Clustering …-and-effect relationship between the operation regimes and the wear level of components. In this study unsupervised clustering technique was …

Major League Baseball. Using attendance data from 2013 to 2019, we explore functional data clustering techniques to detect …

's correlation coefficient, time trend analysis and clustering procedures. Data from Organization for Economic Co-operation and … (CSE). We compared the results of two agglomerative clustering methods and identified groups of similar countries on the …

and a developed branch-and-bound procedure. Moreover, a clustering-based algorithm has been presented that can provide a …

mesoregions. The study used a four-stage methodology, compared the results of two agglomerative clustering methods, and identified …

six classes using a hierarchical clustering algorithm based on five selected spatial characteristics. The six categories …

multiple operations, we employ a clustering approach on 69 firm characteristics and allocate companies to novel economic … to quantify feature importance for clustering methods, finding that size drives differences across classical industries … while book-to-market and financial liquidity variables matter for clustering-based sectors. …

This paper employs k-means clustering, a multidimensional pattern recognition method, to categorize countries using …