Research activity in the field of air pollution forecasting using artificial neural networks
(ANNs) has increased dramatically in recent years. However, the development of ANN …

The use of data-driven techniques such as artificial neural network (ANN) models for
outdoor air pollution forecasting has been popular in the past two decades. However …

Existing studies on the impact of the COVID-19 pandemic on carbon emissions are mainly
based on inter-annual change rate of carbon emissions. This study provided a new way to …

The ability to accurately predict future power demands, power available from renewable
resources and the environmental impact of power generation is vital to the energy sector for …

Abstract Machine learning (ML) methods has recently contributed very well in the
advancement of the prediction models used for energy consumption. Such models highly …

A fuel cut-off injection strategy can be employed during deceleration to increase fuel
efficiency, but NOx is immediately emitted after fuel injection recovery. In this paper, the NOx …

Generally, because the actual operating data tends to be concentrated in local regions due
to the habits of operators and control system design, single models can only train a …

Urban buses are heavy vehicles that move frequently throughout the day, and most of them
are propelled by heavy-duty diesel engines. For these reasons, they have energy and …

Predicting the diffusion coefficient of fluids under nanoconfinement is important for many
applications including the extraction of shale gas from kerogen and product turnover in …

The Chinese government has already been aware of NO x emissions because they are
mainly responsible for a complex air pollution situation in China. The main aim of this …