The history of machine learning (ML) can be traced back to the 1950 s, and its application in
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …

Scientists have extensively studied metallic glasses (MGs) for their excellent properties and
potential applications. However, the limited glass forming ability (GFA) of MGs poses a …

The lubricating oil analysis may be used to verify an assessment of the engine's health and
operational conditions, as well as the need for oil changes. The wide sight of oil …

The CO2 emission issue has triggered the promotion of carbon capture and storage (CCS),
particularly bio-route CCS as a sustainable procedure to capture CO2 using biomass-based …

The prediction accuracy of current mainstream machine learning (ML) models depends on
regulating many hyperparameters. In this paper, a deep forest (DF) model with a few …

Artificial Intelligence (AI) is increasingly being employed in critical decision-making
processes such as medical diagnosis, credit approval, criminal justice, and many more …

The continual development and implementation of machine learning (ML) technology in the
alloy research has proved its great potential in the past few years, making it a prominent …

Tsunamis can trigger internal gravity waves (IGWs) in the ionosphere, perturbing the Total
Electron Content (TEC)-referred to as Traveling Ionospheric Disturbances (TIDs) that are …

Abstract Machine learning (ML) has been extensively studied in predicting the glass-forming
ability of bulk metallic glasses (BMGs). Based on the current state of development of BMGs …

The lack of appropriate data and data imbalance hindered the development of ML models
for identifying novel high-entropy ceramics. To circumvent data imbalance for ML-based …