Context: Recently, the machine learning (ML) field has been rapidly growing, mainly owing
to the availability of historical datasets and advanced computational power. This growth is …

Communication networks are expanding rapidly and becoming increasingly complex. As a
consequence, the conventional rule-based algorithms or protocols may no longer perform at …

The growing success of Machine Learning (ML) is making significant improvements to
predictive models, facilitating their integration in various application fields. Despite its …

Vegetation fires have major impacts on the ecosystem and present a significant threat to
human life. Vegetation fires consists of forest fires, cropland fires, and other vegetation fires …

Random forest is an efficient and accurate classification model, which makes decisions by
aggregating a set of trees, either by voting or by averaging class posterior probability …

Tree ensembles are powerful models that achieve excellent predictive performances, but
can grow to unwieldy sizes. These ensembles are often post-processed (pruned) to reduce …

The big data era has led to an exponential increase in data usage, resulting in significantly
advancements in data-driven domains and data mining. However, due to privacy and …

Driver identification is very important to realizing customized service for drivers and road
traffic safety for electric vehicles and has become a research hotspot in the field of modern …

The use of machine learning algorithms to develop automated analytical methods and smart
sensors has drastically increased in recent years. Although these algorithms often provide …

Prediction of the electronic structure of functional materials is essential for the engineering of
new devices. Conventional electronic structure prediction methods based on density …