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.

Abstract: This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to reflect the profile of this area by focusing more on those subjects that have been given ...

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 ...

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This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the ...

Partitioning methods such as cluster analysis are advantageous in pooling catchments into hydrometric similar regions. They help overcome data shortage in ungauged catchments, which is a common ...

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 ...

The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology ...