Research on different machine learning (ML) has become incredibly popular during the past
few decades. However, for some researchers not familiar with statistics, it might be difficult to …

PM 2.5 is a significant environmental pollutant that damages the environment and
endangers human health. Precise forecast of PM 2.5 concentrations is very important to …

Energy consumption information is a kind of time series with periodicity in many real system,
while the general forecasting methods do not concern periodicity. This paper proposes a …

The use of data-driven methods in fluid mechanics has surged dramatically in recent years
due to their capacity to adapt to the complex and multi-scale nature of turbulent flows, as …

This paper introduces a data-driven ESG assessment approach using blockchain
technology and stochastic multicriteria acceptability analysis (SMAA-2) to address the data …

Digital twins (DTs) are rapidly changing how manufacturing companies leverage the large
volumes of data they generate daily to gain a competitive advantage and optimize their …

Catalytic co-pyrolysis of biomass and plastic wastes is an efficient way for monoaromatic-
rich oil production, while it is difficult to conclude oil evolution rule due to the complex …

Lightweight shape memory polymer (SMP) metamaterials integrated with high strength, high
flexibility, and high recovery stress are highly desired in load carrying structures and …

The experience of graduate degree lecturers in the natural sciences when they switched to
online teaching during the Covid-19 pandemic is described. The shift to online teaching …

Landslides cause significant economic losses and casualties worldwide. However, robust
prediction remains challenging due to the complexity of geological factors contributing to …