Permeability is one of the most critical reservoir characteristics, and its prediction remains a fundamental challenge for both researchers and petroleum engineers. The complexity of predicting ...

Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments. A real-world dataset ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

E-commerce giants are increasingly turning to machine learning (ML) techniques to ensure that their products reach the right audience at the right time, optimizing product discoverability and ...

Proton exchange membrane fuel cells (PEMFCs) are promising for zero-emission vehicles, but their sub-zero start-up capability remains a major hurdle. Freezing of product water inside the membrane ...

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials ...