Abstract: The density-based spatial clustering of applications with noise (DBSCAN) is regarded as a pioneering algorithm of the density-based clustering technique. It provides the ability to handle ...

Abstract: In recent years, several clustering algorithms have been proposed with the aim of mining knowledge from streams of data generated at a high speed by a variety of hardware platforms and ...

Customer Segmentation Analysis using K-Means and DBSCAN clustering to identify customer groups based on income and spending behavior. - khushi28ak/Mall-Customer-Segmentation-Analysis ...

As nations race toward carbon neutrality, the intermittency of wind and solar power poses a major challenge to grid reliability. While hydrogen energy storage systems (HESS) offer a promising buffer ...

Furthermore, to deeply validate the effectiveness of the improved K-means algorithm, we compared its performance against two other prominent clustering algorithms widely used in the literature: ...

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By Dr. Richmond Atuahene1.0 Introduction/ BackgroundGlobalization and digitization are two major trends that will shape the future of nations. Despite the many challenges associated with adapting to ...