Abstract: This work proposes a novel split and kernel-merge clustering (S-KMC), a nonparametric clustering algorithm that combines the strengths of hierarchical clustering, partitional clustering, and ...
Abstract: Wind power pattern clustering can potentially supply information about the effect of incorporating wind farms in smart electrical grid without in-depth analysis and studies of lengthy data.
Library Evolutionary Algorithms for Clustering (LEAC) is a library of genetic algorithms to solve the problem of partition clustering. It includes 22 classification genetic algorithms for solving ...
1 Facultad de Ingeniería, Universidad Andres Bello, Santiago, Chile. 2 Department of Mining Engineering, Universidad de Chile, Santiago, Chile. 3 Advanced Mining Technology Center, Universidad de ...
Time series clustering with a wide variety of strategies and a series of optimizations specific to the Dynamic Time Warping (DTW) distance and its corresponding lower bounds (LBs). There are ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...
A force-matching-based method for supervised machine learning (ML) of coarse-grained (CG) free energy (FE) potentials─known as multiscale coarse-graining via force-matching (MSCG/FM)─is an efficient ...
This study aims to optimize the teaching content of ideological and political courses and guide students to establish correct values. Inspired by Artificial Intelligence, the K-means clustering ...
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