The realm of information entropy research represents a multidisciplinary field, merging mathematical theories with real-world data. At its core, information entropy is the study of uncertainty in ...

Keeping reduction of computation time as the objective, here we present, an entropy query by bagging (EQB)-based AL approach in the extreme learning machine (ELM) framework for remote sensing image ...

Using a new physics-informed machine learning approach, researchers discovered two new high-entropy alloys with extremely low thermal expansion, a new study reports. The approach could represent a ...

Understanding defect dynamics and evolution in high entropy alloys (HEAs) s is complicated due to the wide and intricate configurational space in HEAs. Machine learning techniques have significant ...

Entropy is a confusing concept, but it is also extremely useful for quantifying the properties of complex systems like the human brain. This article attempts to demystify the term.

In an article recently published in the open-access journal npj Computational Materials, researchers discussed the intelligent framework based on machine learning (ML) for finding refractory ...

The concept of entropy—commonly understood as “disorder”—was developed in the 19th century by Sadi Carnot and Rudolf Clausius, who were searching for the most efficient way to convert ...