An extraordinary challenge for real-world applications is traffic sign recognition, which plays
a crucial role in driver guidance. Traffic signals are very difficult to detect using an extremely …

Semisupervised learning holds significant academic and practical importance in the realm of
EEG-based emotion recognition. Currently, a multitude of research endeavors are dedicated …

Existing water quality index (WQI) models assess water quality using a range of
classification schemes. Consequently, different methods provide a number of interpretations …

For data mining tasks on high-dimensional data, feature selection is a necessary pre-
processing stage that plays an important role in removing redundant or irrelevant features …

In order to keep the" good" status of coastal water quality, it is essential to monitor and
assess frequently. The Water quality index (WQI) model is one of the most widely used …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

Researchers often make claims regarding the importance of predictor variables in multiple
regression analysis by comparing standardized regression coefficients (standardized beta …

Abstract Machine learning models have been widely used to study the prediction of heating
and cooling loads in residential buildings. However, most of these methods use the default …

Sign language recognition is challenged by problems, such as accurate tracking of hand
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …

Traffic sign detection (TSD) is a key issue for smart vehicles. Traffic sign recognition (TSR)
contributes beneficial information, including directions and alerts for advanced driver …