[PDF][PDF] Forecasting electric vehicle adoption in the USA using machine learning models
| ABSTRACT Electric vehicles (Electric Vehicles) are at the vanguard of the global
dispensation to sustainable transportation, depicting a pivotal step toward diminishing …
dispensation to sustainable transportation, depicting a pivotal step toward diminishing …
On the relevance of life-cycle CO2 emissions for vehicle purchase decisions
ED Kanberger, A Ziegler - Transportation Research Part D: Transport and …, 2024 - Elsevier
This paper examines individual preferences for a reduction of life-cycle CO 2 emissions in
vehicle purchase decisions. The empirical analysis is based on data from a stated choice …
vehicle purchase decisions. The empirical analysis is based on data from a stated choice …
Analyzing purchase intentions of used electric vehicles through consumer experiences: A structural equation modeling approach
The transition rate to electric vehicles (EVs) has accelerated globally as indicated by a
notable rise in the number of used EVs in the market. However, most existing studies …
notable rise in the number of used EVs in the market. However, most existing studies …
[HTML][HTML] A novel technique for multi-objective sustainable decisions for pavement maintenance and rehabilitation
To maintain pavement in good condition while considering financial costs and sustainability,
it is necessary to develop a comprehensive pavement management plan. Pavement …
it is necessary to develop a comprehensive pavement management plan. Pavement …
Which variables influence electric vehicle adoption?
Understanding the factors that will influence people's preferences for Electric Vehicles (EVs)
over Internal Combustion Engine Vehicles (ICEVs) is crucial. A discrete choice experiment …
over Internal Combustion Engine Vehicles (ICEVs) is crucial. A discrete choice experiment …
Investigating of machine learning's capability in enhancing traffic simulation models
The development of agent-based modeling in traffic simulation allows for the modeling of
traveler movement and decision making using predefined rules and variables. Nonetheless …
traveler movement and decision making using predefined rules and variables. Nonetheless …
[HTML][HTML] Identifying the key factors of intermodal travel using interpretative ensemble learning
Intermodal travel is considered an effective method for achieving sustainable urban
transportation. Understanding the factors influencing intermodal travel is crucial. Due to the …
transportation. Understanding the factors influencing intermodal travel is crucial. Due to the …
Measurement of Regional Electric Vehicle Adoption Using Multiagent Deep Reinforcement Learning
This study explores the socioeconomic disparities observed in the early adoption of Electric
Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy …
Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy …
Travel mode choice prediction: develo** new techniques to prioritize variables and interpret black-box machine learning techniques
ABSTRACT Travel Mode Choice (TMC) prediction is vital for forecasting travel demand and
transportation planning. To be helpful for those purposes, one needs to know with high …
transportation planning. To be helpful for those purposes, one needs to know with high …
MI-OPTNET: AN OPTIMIZED DEEP LEARNING FRAMEWORK FOR MYOCARDIAL INFARCTION DETECTION
The conventional means of myocardial infarction (MI) detection using a 12-lead
electrocardiogram (ECG) system include a pretrained network and machine learning …
electrocardiogram (ECG) system include a pretrained network and machine learning …