Evaluation of energy-environmental-economic benefits of CNG taxi policy using multi-task deep-learning-based microscopic models and big trajectory data
Natural gas has been widely recognized as an economic and environmental-friendly
alternative fuel in the transport sector. Many cities have implemented the policy to …
alternative fuel in the transport sector. Many cities have implemented the policy to …
[HTML][HTML] Modeling of CO emissions from traffic vehicles using artificial neural networks
Traffic emissions are considered one of the leading causes of environmental impact in
megacities and their dangerous effects on human health. This paper presents a hybrid …
megacities and their dangerous effects on human health. This paper presents a hybrid …
High-fidelity modeling of light-duty vehicle emission and fuel economy using deep neural networks
The transportation sector contributes significantly to emissions and air pollution globally.
Emission models of modern vehicles are important tools to estimate the impact of …
Emission models of modern vehicles are important tools to estimate the impact of …
Integrated MOVES model and machine learning method for prediction of CO2 and NO from light-duty gasoline vehicle
With rapid urbanization and industrialization, the number of light-duty gasoline vehicles
(LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic …
(LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic …
Estimation of transport CO2 emissions using machine learning algorithm
S Li, Z Tong, M Haroon - Transportation Research Part D: Transport and …, 2024 - Elsevier
This study investigates carbon dioxide emissions from light-duty diesel trucks using a
portable emission measurement system (PEMS) and a global positioning system. Two …
portable emission measurement system (PEMS) and a global positioning system. Two …
A microscopic model of vehicle co₂ emissions based on deep learning—A spatiotemporal analysis of taxicabs in Wuhan, China
It is important to assess environmental impact of intelligent transportation systems, and
hence developing a vehicle emission model with high accuracy has been a long-standing …
hence developing a vehicle emission model with high accuracy has been a long-standing …
[HTML][HTML] Using deep learning techniques to forecast environmental consumption level
Artificial intelligence is a promising futuristic concept in the field of science and technology,
and is widely used in new industries. The deep-learning technology leads to performance …
and is widely used in new industries. The deep-learning technology leads to performance …
[HTML][HTML] Predicting CO2 Emission Footprint Using AI through Machine Learning
Y Meng, H Noman - Atmosphere, 2022 - mdpi.com
Adequate CO2 is essential for vegetation, but industrial chimneys and land, space and
oceanic vehicles exert tons of excessive CO2 and are mostly responsible for the …
oceanic vehicles exert tons of excessive CO2 and are mostly responsible for the …
[HTML][HTML] Machine-learning-based carbon dioxide concentration prediction for hybrid vehicles
The current understanding of CO2 emission concentrations in hybrid vehicles (HVs) is
limited, due to the complexity of the constant changes in their power-train sources. This …
limited, due to the complexity of the constant changes in their power-train sources. This …
Segment-Based CO₂ Emission Evaluations From Passenger Cars Based on Deep Learning Techniques
N Niroomand, C Bach, M Elser - IEEE Access, 2021 - ieeexplore.ieee.org
The overall level of emissions from the Swiss passenger cars is strongly dependent on the
fleet composition. Despite technology improvements, the Swiss passenger cars fleet …
fleet composition. Despite technology improvements, the Swiss passenger cars fleet …