Abstract: When processing massive data, existing classification methods frequently take too long to compute, making their performance challenging to satisfy the actual needs of big data applications.

This project applies various machine learning models—especially XGBoost—to classify ECG heartbeat signals from the MIT-BIH Arrhythmia Database. Advanced metaheuristic optimization algorithms are used ...

Abstract: Network traffic, as an important element of modern network, requires proper classification to ensure security, performance, and compliance. Analysis of service and capacity planning lies on ...

A data-driven inventory management solution using ABC classification and Prophet forecasting to analyze demand patterns. It computes key parameters like reorder point, optimal reorder quantity, and ...

Department of Chemistry, University of Illinois at Urbana─Champaign, Urbana, Illinois 61801, United States Department of Chemistry, Rice University, Houston, Texas 77005, United States Department of ...

Objective: This study evaluated the diagnostic accuracy of the 2012 SLICC and 2019 EULAR/ACR criteria in Chinese cSLE patients and aimed to develop an optimized classification schema based on the 2019 ...

What if the key to unlocking the full potential of your AI-powered workflows lies not in adding more tools but in optimizing the ones you already have? For developers and teams using Claude Code, the ...

Prior to the start of the 21st century, there were no agreed unifying principles to guide the establishment and development of Para sport classification systems. Classification policies and procedures ...