Since canonical machine learning algorithms assume that the dataset has equal number of
samples in each class, binary classification became a very challenging task to discriminate …

Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …

Despite over two decades of progress, imbalanced data is still considered a significant
challenge for contemporary machine learning models. Modern advances in deep learning …

Class imbalance is an active research area in the machine learning community. However,
existing and recent literature showed that class overlap had a higher negative impact on the …

Real-time prediction of the rock mass class in front of the tunnel face is essential for the
adaptive adjustment of tunnel boring machines (TBMs). During the TBM tunnelling process …

In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …

Rockburst is a common dynamic geological hazard, severely restricting the development
and utilization of underground space and resources. As the depth of excavation and mining …

With the spectacular growth of air traffic demand expected over the next two decades, the
safety of the air transportation system is of increasing concern. In this paper, we facilitate the …

Introduction Golgi is one of the components of the inner membrane system in eukaryotic
cells. Its main function is to send the proteins involved in the synthesis of endoplasmic …

Increase in the number of new chemicals synthesized in past decades has resulted in
constant growth in the development and application of computational models for prediction …