Abstract Gradient Boosted Decision Trees (GBDT's) are a powerful tool for classification and
regression tasks in Big Data. Researchers should be familiar with the strengths and …

Driving style recognition provides an effective way to understand human driving behaviors
and thereby plays an important role in the automotive sector. However, most works fail to …

Establishing a computational model for accurate prediction of reference crop
evapotranspiration (ET 0) is critical for regional water resources planning and irrigation …

This study presents two machine learning models, namely, the light gradient boosting
machine (LightGBM) and categorical boosting (CatBoost), for the first time for predicting …

Driving style detection is an essential real-world requirement in diverse contexts, such as
traffic safety, car insurance and fuel consumption optimization. However, the existing …

Transportation activity recognition (TAR) provides valuable support for intelligent
transportation applications, such as urban transportation planning, driving behavior …

This study explores the performance augmentation of a regenerative counterflow indirect
evaporative cooler (RCFIEC) both experimentally and numerically. A counter flow heat/mass …

The monkeypox virus poses a novel public health risk that might quickly escalate into a
worldwide epidemic. Machine learning (ML) has recently shown much promise in …

In order to reduce the adverse effects of concrete on the environment, options for eco-
friendly and green concretes are required. For example, geopolymers can be an …

Driving style can significantly affect the energy consumption, battery lifespan, and driving
economy of electric vehicles. In this context, this paper proposes a novel driving style-aware …