With global warming, and internal combustion engine emissions as the main global non-
industrial emissions, how to further optimize the power performance and emissions of …

This study deals with artificial neural network (ANN) modeling of a gasoline engine to predict
the brake specific fuel consumption, effective power and exhaust temperature of the engine …

The use of computational models for internal combustion engine development is ubiquitous.
Numerical simulations using simpler to complex physical models can predict engine's …

This study deals with artificial neural network (ANN) modelling of a gasoline engine to
predict the brake specific fuel consumption, brake thermal efficiency, exhaust gas …

Abstract Machine learning (ML) models can accelerate the development of efficient internal
combustion engines. This study assessed the feasibility of data-driven methods toward …

Increasing the application of machine learning algorithms in engine development has the
potential to reduce the number of experimental runs and the computation cost of …

The sole intention of this research work is to examine the performance and pollutant
emissions of a four-stroke SI engine, allowed to operate under specific conditions with …

This study investigates the use of ANN (artificial neural networks) modelling to predict BSFC
(break specific fuel consumption), exhaust emissions that are CO (carbon monoxide) and …

This study details the artificial neural network (ANN) modelling of a diesel engine to predict
the torque, power, brake-specific fuel consumption and pollutant emissions, including …

The experiment about gasoline fuel plus oxygen-enriched combustion (OEC) technology is
conducted on a combined injection engine in this paper. OEC is an effective in-cylinder …