Naslov
Energy Potentials of Agricultural Biomass and the Possibility of Modelling Using RFR and SVM Models

Autori
Brandić, Ivan ; Antonović, Alan ; Pezo, Lato ; Matin, Božidar ; Krička, Tajana ; Jurišić, Vanja ; Špelić, Karlo ; Kontek, Mislav ; Kukuruzović, Juraj ; Grubor, Mateja ; Matin, Ana

Izvornik
Energies (1996-1073) 16 (2023); 690, 10

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
agricultural biomass ; higher heating value ; machine learning ; estimation ; energy potential

Sažetak
Agricultural biomass is one of the most important renewable energy sources. As a byproduct of corn, soybean and sunflower production, large amounts of biomass are produced that can be used as an energy source through conversion. In order to assess the quality and the possibility of the use of biomass, its composition and calorific value must be determined. The use of nonlinear models allows for an easier estimation of the energy properties of biomass concerning certain input and output parameters. In this paper, RFR (Random Forest Regression) and SVM (Support Vector Machine) models were developed to determine their capabilities in estimating the HHV (higher heating value) of biomass based on input parameters of ultimate analysis. The developed models showed good performance in terms of HHV estimation, confirmed by the coefficient of determination for the RFR (R2 = 0.79) and SVM (R2 = 0.93) models. The developed models have shown promising results in accurately predicting the HHV of biomass from various sources. The use of these algorithms for biomass energy prediction has the potential for further development.

Izvorni jezik
Engleski

Znanstvena područja
Biotehnologija

POVEZANOST RADA