Development of greenhouse gas emissions model for 2014-2017 heavy-and medium-duty vehicle compliance

B Lee, L Quinones, J Sanchez - 2011 - sae.org
Of all existing modes of transportation, onroad motor vehicles are the largest contributor to
greenhouse gas emissions and fuel usage. The Environmental Protection Agency and the …

[HTML][HTML] Artificial intelligence and machine learning-based decision support system for forecasting electric vehicles' power requirement

SK Jauhar, S Sethi, SS Kamble, S Mathew… - … Forecasting and Social …, 2024 - Elsevier
Increasing pollution is causing adverse environmental effects, leading to increased interest
in combating this issue. There has been a significant interest in minimizing the pollution …

Prediction of instantaneous real-world emissions from diesel light-duty vehicles based on an integrated artificial neural network and vehicle dynamics model

J Seo, B Yun, J Park, J Park, M Shin, S Park - Science of the Total …, 2021 - Elsevier
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 …

Energy consumption prediction of electric vehicles based on big data approach

F Foiadelli, M Longo… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
An accurate prediction of the electric vehicles (EVs) energy consumption is the crucial
requirement to deliver the promise of the green energy solution for relieving the concerns …

Analysis of alternative fuel vehicle (AFV) adoption utilizing different machine learning methods: a case study of 2017 NHTS

J Jia - IEEE Access, 2019 - ieeexplore.ieee.org
Alternative fuel vehicles (AFVs) are considered as the one of policies towards the
sustainable transportation with low fossil fuel consumption and greenhouse gas emission …

Vehicle fuel consumption prediction method based on driving behavior data collected from smartphones

Y Yao, X Zhao, C Liu, J Rong, Y Zhang… - Journal of Advanced …, 2020 - Wiley Online Library
Transportation is an important factor that affects energy consumption, and driving behavior is
one of the main factors affecting vehicle fuel consumption. The purpose of this paper is to …

[HTML][HTML] Deep learning LSTM recurrent neural network model for prediction of electric vehicle charging demand

J Shanmuganathan, AA Victoire, G Balraj, A Victoire - Sustainability, 2022 - mdpi.com
The immense growth and penetration of electric vehicles has become a major component of
smart transport systems; thereby decreasing the greenhouse gas emissions that pollute the …

[图书][B] Electric Vehicles in Energy Systems

The transportation sector utilizes a considerable amount of energy worldwide; therefore, it
has a significant impact on today's energy systems. In recent years, electric vehicles (EVs) …

Emissions predictive modelling by investigating various neural network models

WK Yap, V Karri - Expert Systems with Applications, 2012 - Elsevier
This paper presents a two-stage emissions predictive model developed by investigating
common feedforward neural network models. The first stage model involves predicting …

[HTML][HTML] Using machine learning methods to predict electric vehicles penetration in the automotive market

S Afandizadeh, D Sharifi, N Kalantari… - Scientific Reports, 2023 - nature.com
Electric vehicles (EVs) have been introduced as an alternative to gasoline and diesel cars to
reduce greenhouse gas emissions, optimize fossil fuel use, and protect the environment …