Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...
U.S. soldiers fire an M777 Howitzer during an operational exercise at Mission Support Site Conaco, Syria, Dec. 4, 2022. (Sgt. Julio Hernandez/Army) The U.S. Army is looking for companies that can ...
No one likes flies, especially if they’re gathering inside your home. That’s just what occurs in the fall when cluster flies begin to look for protected areas to overwinter. “As the temperatures drop ...
In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...
1 School of Computer Science and Technology, Yibin University, Yibin, China 2 School of Computer and Software, Southwest Petroleum University, Chengdu, China Ever since Density Peak Clustering (DPC) ...
Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...
Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...
About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a new feature, billions of dollars this, AI agents that. It has been non-stop ...
Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback