Nature

A hybrid machine learning approach for reliably predicting surface roughness in CNC turning operations

Surface roughness in CNC turning is a pivotal quality metric shaping functional performance, service life and production cost. This study investigates data-driven prediction of arithmetic mean surface ...
Nature

Hybrid machine learning and Gaussian process for antenna parameter estimation

This paper presents a hybrid method of combining the Random Forest (RF) algorithm in machine learning (ML) and the Gaussian process (GP) to design microstrip patch antennas at any frequency from 0.6 ...
Phys.org

Automating microfluidic chip design: Hybrid approach combines machine learning with fluid mechanics

Researchers led by Assoc. Prof. Dr. Savaş Taşoğlu from the Department of Mechanical Engineering at Koç University have developed a new, open-access and machine learning-assisted design tool aimed at ...
AZoNano

Machine Learning Reveals Hidden Nanophotonic Resonances In Silicon-Gold Nanopillars

Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...