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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Bibliographic Details
Published in:	Fuel (Guildford) Vol. 320; p. 123971
Main Authors:	Yaka, Havva, Insel, Mert Akin, Yucel, Ozgun, Sadikoglu, Hasan
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 15.07.2022 Elsevier BV
Subjects:	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
Online Access:	Get full text
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