Abstract: The density peaks clustering (DPC) algorithm is a density-based clustering method that effectively identifies clusters with uniform densities. However, if the datasets have uneven density, ...
Across industries, HR leaders are facing a new reality: Machines are not just supporting HR—they are now shaping it. Generative AI is writing job descriptions, scanning resumes, curating training ...
ABSTRACT: Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In ...
ABSTRACT: Spatial transcriptomics is undergoing rapid advancements and iterations. It is a beneficial tool to significantly enhance our understanding of tissue organization and relationships between ...
Editor’s note: This story is part of Peak, The Athletic’s desk covering leadership, personal development and performance through the lens of sports. Follow Peak here. Joe Boylan worked in the NBA for ...
The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...
Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...
If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.
Researchers have used the jellyfish search algorithm to optimize solar PV distributed generation placement and sizing. They have tested the algorithm on an IEEE 33-bus system, with one, two, or three ...
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