In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

Ensemble learning combines several individual models to obtain better generalization
performance. Currently, deep learning architectures are showing better performance …

As an algorithm with excellent performance, convolutional neural network has been widely
used in the field of image processing and achieved good results by relying on its own local …

Rapid Internet use growth and applications of diverse military have managed researchers to
develop smart systems to help applications and users achieve the facilities through the …

Being able to predict the churn rate is the key to success for the telecommunication industry.
It is also important for the telecommunication industry to obtain a high profit. Thus, the …

Southeast Asia (SEA) is a region affected by landslide and wildfire; however, few studies on
susceptibility modeling for the two hazards together have been conducted for this region …

Road traffic accidents are one of the world's most serious problems, as they result in
numerous fatalities and injuries, as well as economic losses each year. Assessing the …

Smartness and IoT along with machine learning (ML) lead the research directions
nowadays. Smart city, smart campus, smart home, smart vehicle, etc; or if we call it “Smart x” …

Machine learning (ML) and the internet of things (IoT) are among the most booming
research directions. Smart cities, smart campuses (SCs), smart homes, smart cars, early …

Accurate prediction of network traffic is an important premise in network management and
congestion control. In order to improve the prediction accuracy of network traffic, a prediction …