In order to provide an efficient conversion and utilization of solar power, solar radiation datashould be measured continuously and accurately over the long-term period. However, the measurement ofsolar radiation is not available to all countries in the world due to some technical and fiscal limitations. Hence,several studies were proposed in the literature to find mathematical and physical mod...

We develop the heuristic PROBI for the probabilistic Euclidean k-median problem based on a coreset construction by Lammersen et al. [28]. Our algorithm computes a summary of the data and then uses an adapted version of k-means++ [5] to compute a good solution on the summary. The summary is maintained in a data stream, so PROBI can be used in a data stream setting on very large data sets. We exp...

Hierarchical clustering methods have attracted much attention by giving the user a maximum amount of flexibility. Rather than requiring parameter choices to be predetermined, the result represents all possible levels of granularity. In this paper a hierarchical method is introduced that is fundamentally related to partitioning methods, such as k-medoids and k-means as well as to a density based...

This paper investigates the following natural greedy procedure for clustering in the bi-criterion setting: iteratively grow a set of centers, in each round adding the center from a candidate set that maximally decreases clustering cost. In the case of k-medians and k-means, the key results are as follows. • When the method considers all data points as candidate centers, then selecting O(k log(1...

Abstract We propose two new algorithms for clustering graphs and networks. The first, called K?algorithm , is derived directly from the k -means algorithm. It applies similar iterative local optimization but without need to calculate means. inherits properties of in terms both good capability tendency get stuck at a optimum. second algorithm, M-algorithm gradually improves on results K -algorit...