Vehicular emissions prediction with CART-BMARS hybrid models
Vehicular emission models play a key role in the development of reliable air quality
modeling systems. To minimize uncertainties associated with these models, it is essential to …
modeling systems. To minimize uncertainties associated with these models, it is essential to …
Predictive analysis of in-vehicle air quality monitoring system using deep learning technique
In-vehicle air quality monitoring systems have been seen as promising paradigms for
monitoring drivers' conditions while they are driving. This is because some in-vehicle cabins …
monitoring drivers' conditions while they are driving. This is because some in-vehicle cabins …
The Development of CO2 Instantaneous Emission Model of Full Hybrid Vehicle with the Use of Machine Learning Techniques
Road transport contributes to almost a quarter of carbon dioxide emissions in the EU. To
analyze the exhaust emissions generated by vehicle flows, it is necessary to use specialized …
analyze the exhaust emissions generated by vehicle flows, it is necessary to use specialized …
Applied machine learning in industry 4.0: Case-study research in predictive models for black carbon emissions
J Rubio-Loyola, WRS Paul-Fils - Sensors, 2022 - mdpi.com
Industry 4.0 constitutes a major application domain for sensor data analytics. Industrial
furnaces (IFs) are complex machines made with special thermodynamic materials and …
furnaces (IFs) are complex machines made with special thermodynamic materials and …
Prediction of energy consumption for new electric vehicle models by machine learning
A Fukushima, T Yano, S Imahara, H Aisu… - IET Intelligent …, 2018 - Wiley Online Library
Recommending suitable charging spots to drivers on expressways for both charging
equipment and electric vehicles (EVs) is an important issue for the spread of EVs. Therefore …
equipment and electric vehicles (EVs) is an important issue for the spread of EVs. Therefore …
Can UK passenger vehicles be designed to meet 2020 emissions targets? A novel methodology to forecast fuel consumption with uncertainty analysis
Vehicle manufacturers are required to reduce their European sales-weighted emissions to
95 g CO 2/km by 2020, with the aim of reducing on-road fleet fuel consumption …
95 g CO 2/km by 2020, with the aim of reducing on-road fleet fuel consumption …
Characterizing carbon emissions from China V and China VI gasoline vehicles based on portable emission measurement systems
On-road vehicle has been a prominent emission source, hence a key target of control for
environment, health, and climate concerns. While considerable efforts have been made to …
environment, health, and climate concerns. While considerable efforts have been made to …
Vehicle energy dataset (VED), a large-scale dataset for vehicle energy consumption research
We present Vehicle Energy Dataset (VED), a large-scale dataset of fuel and energy data
collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures …
collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures …
A comparative study on fuel consumption prediction methods of heavy-duty diesel trucks considering 21 influencing factors
J Gong, J Shang, L Li, C Zhang, J He, J Ma - Energies, 2021 - mdpi.com
With increasingly prominent environmental problems, controlling automobile exhaust has
become essential to the environment. The fuel consumption of transportation is the critical …
become essential to the environment. The fuel consumption of transportation is the critical …
On modeling microscopic vehicle fuel consumption using radial basis function neural network
Energy conservation is one of the central challenges for the transportation system today. A
variety of microscopic vehicle fuel consumption models have been developed to support eco …
variety of microscopic vehicle fuel consumption models have been developed to support eco …