Performance Evaluation of Diesel engine by feature selection of Exhaust using Machine Learning Algorithm
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 12
Abstract
In Diesel Engines, it has always been a field of interest, the control of Air-Fuel Ratio (AFR) in its transient operating conditions. Exhaust gas related to emission of CO2, NOx, PM, CO and unburned HC, together with the consumption of fossil fuels, gives a lot of interest at Global level. Thus in this work an attempt is made to evaluate the Performance of Diesel Engine by considering parameters like CO2, NOx, PM, CO and unburned HC for better efficiency using Machine Learning algorithm like Genetic Algorithm.
Authors and Affiliations
Agil Lukose, Addepalli VN Krishna
Keywords
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