A comparison of machine learning algorithms for estimation of higher heating values of biomass and fossil fuels from ultimate analysis

•HHV of fuels are estimated from ultimate analysis on a dry, ash-free basis.•Performance of several machine learning algorithms are evaluated.•Van Krevelen diagram of several classes of fuels was plotted with a large dataset.•The proposed RFR and DTR models yielded the best results for HHV estimatio...

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Vydáno v:	Fuel (Guildford) Ročník 320; s. 123971
Hlavní autoři:	Yaka, Havva, Insel, Mert Akin, Yucel, Ozgun, Sadikoglu, Hasan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 15.07.2022 Elsevier BV
Témata:	Algae Algorithms Biomass Calorific value Charcoal Computer applications Datasets Fossil fuels Fuel oils Fuel technology Gaseous fuels Gasoline Heating Higher heating value Learning algorithms Machine learning Mathematical models Municipal solid waste Municipal waste management Natural gas Performance evaluation Polynomials Regression Regression analysis Solid waste management Statistical analysis CC ANN DTR C Higher heating value ABE AAE DAF GPR H Regression GP RMSE Biomass N SVR O MAE S N-RMSE HHV Machine learning FC RFR
ISSN:	0016-2361, 1873-7153
On-line přístup:	Získat plný text
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