Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...

Abstract: Clustering has attracted more and more attention as one of the most fundamental techniques in the field of unsupervised learning. To deal with nonlinear problems, clustering methods have ...

Researchers have developed an energy-saving control strategy for intelligent connected plug-in hybrid electric vehicles that ...

Abstract: The palette mode is a specialized coding tool for coding screen content video in Alliance for Open Media Video 1 (AV1), and K-means clustering is a necessary step in the palette mode.

This study investigates the application of advanced clustering methods to geological fracture analysis in the Baba Kohi anticline, located in the folded Zagros region of southwest Iran. The primary ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable strain on ...

A recent study published March 17 by researchers at the University of Michigan details the unique experiences of Black women on online dating platforms. Researchers examined the challenges Black women ...

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...

This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...