Predicting the properties of liquid energy carriers using machine learning tools
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Insinööritieteiden korkeakoulu |
Bachelor's thesis
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Authors
Date
2021-05-01
Department
Major/Subject
Energia- ja ympäristötekniikka
Mcode
ENG3042
Degree programme
Insinööritieteiden kandidaattiohjelma
Language
en
Pages
28
Series
Description
Supervisor
Alanne, KariThesis advisor
Toldy, ArpadKeywords
octane number, neural network, QSPR, fuel property prediction, biofuel, gasoline