An Experimental Selection of Deep Neural Network Hyperparameters for Engine Emission Prognosis
Author:
Affiliation:
1. Institute of Data Science and Digital Technologies Vilnius University,Vilnius,Lithuania
2. Institute of Mechanical science Vilnius Gediminas Technical University,Vilnius,Lithuania
Funder
Research Council of Lithuania (LMTLT)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10542546/10542531/10542607.pdf?arnumber=10542607
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1. Ecology in Transport: Problems and Solutions
2. Perspectives on decarbonizing the transport sector in the EU-28
3. Experimental investigation of acoustic agglomeration of diesel engine exhaust particles using new created acoustic chamber
4. Impact of Simulated Biogas Compositions (CH4 and CO2) on Vibration, Sound Pressure and Performance of a Spark Ignition Engine
5. Engine Vibration Data Increases Prognosis Accuracy on Emission Loads: A Novel Statistical Regressions Algorithm Approach for Vibration Analysis in Time Domain
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