Results 21 to 30 of about 15,200 (191)

Real-driving CO2, NOx and fuel consumption estimation using machine learning approaches

open access: yesNext Energy, 2023
Real driving emissions (RDE) testing are gaining attention for monitoring and regulatory purposes because of providing more realistic emission and fuel consumption measurements compared to laboratory tests. This study aims to develop machine learning (ML)
G M Hasan Shahariar   +7 more
doaj   +1 more source

A Comparative Study of Actual Fuel Consumption and the Predicted Fuel Consumption of the Tractor with Chisel Plow

open access: yes, 2021
A field experiment was conducted during December 2019, at the Demonstration Farm of the Faculty of Natural Resources and Environmental Studies, University of Alsalam. The objective was to compare the actual fuel consumption and the predicted fuel consumption of tractor with chisel plow.
Suliman, Ayman Hassan   +2 more
openaire   +2 more sources

Research on energy management strategy of fuel cell power generation system based on Grey–Markov chain power prediction

open access: yesEnergy Reports, 2021
Fuel cell power generation system is a potential renewable power source. To reduce hydrogen consumption and enhance the dynamic performance of the system, Grey–Markov chain power prediction energy management strategy for fuel cell power generation ...
Zhichao Fu   +5 more
doaj   +1 more source

Predicting fuel energy consumption during earthworks [PDF]

open access: yesJournal of Cleaner Production, 2016
This research contributes to the assessment of on-site fuel consumption and the resulting carbon dioxide emissions due to earthworks-related processes in residential building projects, prior to the start of the construction phase. Several studies have been carried out on this subject, and have demonstrated the considerable environmental impact of ...
TRANI, MARCO LORENZO AGOSTINO   +3 more
openaire   +3 more sources

LHV Predication Models and LHV Effect on the Performance of CI Engine Running with Biodiesel Blends [PDF]

open access: yes, 2013
The heating value of fuel is one of its most important physical properties, and is used for the design and numerical simulation of combustion processes within internal combustion (IC) engines. Recently, there has been a significant increase in the use of
Gu, Fengshou   +7 more
core   +1 more source

Experimental validation of equilibria in fuel cells with dead-ended anodes [PDF]

open access: yes, 2013
This paper investigates the nitrogen blanketing front during the dead-ended anode (DEA) operation of a PEM fuel cell. Surprisingly the dynamic evolution of nitrogen and water accumulation in the dead-ended anode (DEA) of a PEM fuel cell arrives to a ...
Anna G. Stefanopoulou   +9 more
core   +1 more source

A Multitask Learning Framework for Predicting Ship Fuel Oil Consumption

open access: yesIEEE Access, 2023
Predicting the ship fuel consumption constitutes a prerequisite for speed, trim, and voyage optimization. In spite of the rise of deep learning and transformers in many domains, research works train shallow machine learning (ML) algorithms for predicting ship fuel oil consumption (FOC).
Loukas Ilias   +3 more
openaire   +2 more sources

Machine Learning and Predictive Analysis of Fossil Fuels Consumption in Mid-Term [PDF]

open access: yesICST Transactions on Scalable Information Systems, 2017
In economies that are dependent on fossil fuel revenues, Realization of long-term plans, mid-term and annual budgeting requires a fairly accurate estimation of the amount of consumption and its price fluctuations. Accordingly, the present study is using machine learning techniques to predict the usage of fossil fuels (Diesel, Black oil, Heating oil ...
Mahmood Amerion   +3 more
openaire   +3 more sources

Multilayer Perceptron Method to Estimate Real-World Fuel Consumption Rate of Light Duty Vehicles

open access: yesIEEE Access, 2019
The actual driving condition and fuel consumption rate gaps between lab and real-world are becoming larger. In this paper, we demonstrate an approach to determine the most important factors that may influence the prediction of real-world fuel consumption
Yawen Li   +5 more
doaj   +1 more source

Self-labelling of tugboat operation using unsupervised machine learning and intensity indicator

open access: yesMaritime Transport Research, 2023
The actual operational data, such as a time sequence of fuel consumption and speed, is usually unlabeled or not associated with a specific activity like tugging or cruising.
Januwar Hadi   +2 more
doaj   +1 more source

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