A new machine learning framework called Replication-Free Data Management uses Random Forest classification and conditional scheduling to eliminate duplicate records...

A new interpretable machine learning study shows that warming in Northeast China's frozen soils decreases with depth, with longwave radiation,...

Researchers paired a validated PLAXIS 3D finite element model with kernel-based Support Vector Machines to predict soil bearing capacity with...

Researchers have shown that mid-infrared spectroscopy combined with machine learning can rapidly and cheaply identify the host species of Culex...

A machine learning benchmark of 350 Malaysian IPOs finds that a regularized linear support vector model outperforms complex ensembles and...

A new survey argues that in 6G networks, machine learning must contend with its own feedback loops, non-stationary data, and...

An interpretable machine learning framework using Random Forest and SHAP analysis has delivered reliable permeability predictions for the tight, heterogeneous...

A multi-omics study of over 53,000 UK Biobank participants identifies 25 proteins, including galectin-3, that predict and may drive the...

Researchers have shown that atmospheric diabatic heating over the Southeast Asian low-latitude highlands, combined with physically constrained machine learning models,...

An international research team has built an open, reproducible machine learning workflow that classifies honey seasons as poor, moderate, or...