Burning fossil fuels results in emissions of carbon dioxide (CO2), which significantly
contributes to atmospheric changes and climate disturbances. Consequently, people are …

On-road carbon dioxide (CO2) emissions from light-duty diesel trucks (LDDTs) are greatly
affected by driving conditions, which may be better predicted with the sequence deep …

Enhancing gasoline detergency is pivotal for enhancing fuel efficiency and mitigating
exhaust emissions in gasoline vehicles. This study investigated gasoline vehicle emission …

How to select a suitable spatial weighting scheme for convolutional graph neural networks
(ConvGNNs) is challenging. In this study, we propose a ConvGNN, termed learnable graph …

Prediction of short-term traffic flow has been examined recently, but little attention has been
paid to the prediction of citywide turning traffic flow at intersections. Based on an in-depth …

Advanced visualization techniques can be useful for a better understanding of driving
behavior and vehicle emissions in real-time. This study used classic and sparse HJ-biplots …

Microscopic emission estimation based on driving states plays a crucial role in controlling
the pollution of on-road vehicles. Existing research has evolved from fitting nonlinear models …

Personal vehicles play a significant role in contributing to the issue of global warming.
Gasoline used in cars emits an estimated 24 pounds of carbon dioxide and other …

The qualification work on the topic" Research and development of an information system for
CO2 emissions during the operation of trucks at food enterprises" was developed by a …