Deep learning model based CO2 emissions prediction using vehicle telematics sensors data
Climate change is one of the greatest environmental hazards to mankind. The emission of
greenhouse gases has resulted in a continuous increase in the temperature of the …
greenhouse gases has resulted in a continuous increase in the temperature of 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 …
[HTML][HTML] Predicting CO2 Emissions from Traffic Vehicles for Sustainable and Smart Environment Using a Deep Learning Model
AH Al-Nefaie, THH Aldhyani - Sustainability, 2023 - mdpi.com
Burning fossil fuels results in emissions of carbon dioxide (CO2), which significantly
contributes to atmospheric changes and climate disturbances. Consequently, people are …
contributes to atmospheric changes and climate disturbances. Consequently, people are …
[HTML][HTML] Forecasting carbon dioxide emissions of light-duty vehicles with different machine learning algorithms
Accurate estimation of fuel consumption and emissions is crucial for assessing the impact of
materials and stringent emission control techniques on climate change, particularly in the …
materials and stringent emission control techniques on climate change, particularly in the …
Vehicle emission forecasting based on wavelet transform and long short-term memory network
This paper proposes a time series model based on wavelet transform and long short-term
memory (LSTM) network to forecast vehicle emission. It implements the semi-supervised …
memory (LSTM) network to forecast vehicle emission. It implements the semi-supervised …
[HTML][HTML] A Deep Learning Micro-Scale Model to Estimate the CO2 Emissions from Light-Duty Diesel Trucks Based on Real-World Driving
R Zhang, Y Wang, Y Pang, B Zhang, Y Wei, M Wang… - Atmosphere, 2022 - mdpi.com
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 …
affected by driving conditions, which may be better predicted with the sequence deep …
[HTML][HTML] Analysis and prediction model of fuel consumption and carbon dioxide emissions of light-duty vehicles
Due to the alarming rate of climate change, fuel consumption and emission estimates are
critical in determining the effects of materials and stringent emission control strategies. In this …
critical in determining the effects of materials and stringent emission control strategies. In this …
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 …
Parallel attention-based LSTM for building a prediction model of vehicle emissions using PEMS and OBD
H Xie, Y Zhang, Y He, K You, B Fan, D Yu, B Lei… - Measurement, 2021 - Elsevier
Portable emission measurement system (PEMS) testing, which is the most accurate
measurement method for vehicle emissions, has been included into the regulations of …
measurement method for vehicle emissions, has been included into the regulations of …
Prediction of instantaneous real-world emissions from diesel light-duty vehicles based on an integrated artificial neural network and vehicle dynamics model
This paper presents a road vehicle emission model that integrates an artificial neural
network (ANN) model with a vehicle dynamics model to predict the instantaneous carbon …
network (ANN) model with a vehicle dynamics model to predict the instantaneous carbon …