Estimation of Biomass Fuels' HHVs Based on Ultimate and Proximate Analysis and Their Combination Data Using MLP-ANN Models
Yazarlar (4)
Sevilay Demirci
Doç. Dr. Vedat ADIGÜZEL Kafkas Üniversitesi, Türkiye
Muhammet Ali Karabulut
Kafkas Üniversitesi, Türkiye
Kafkas Üniversitesi, Türkiye
Prof. Dr. Fikret AKDENİZ Kafkas Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | SOLID FUEL CHEMISTRY (Q4) | ||
| Dergi ISSN | 0361-5219 Dergi Bilgileri (2022) | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2022 |
| Cilt / Sayı / Sayfa | 56 / 0 / – | DOI | 10.3103/S0361521923010123 |
| Makale Linki | https://link.springer.com/article/10.3103/S0361521923010123 | ||
| UAK Araştırma Alanları |
Fen Bilimleri ve Matematik
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| Özet |
| The most important thing to know when investigating the feasibility of energy generation from biomass materials is the higher heating values (HHVs). 12 biochars were obtained from zeyrek pulp by hydrothermal carbonization method. Fuel properties (proximate, ultimate and calorific value) and structural properties (by IR spectroscopy) of the obtained biochars were determined. To predict HHVs of biomass, the multi-layer perceptron artificial neural network (MLP-ANN) technique is used. For this purpose, 66 real data points were extracted from both our data and reliable references for the model’s training and validation. Based on input data from the proximate analysis, ultimate analysis and combined proximate-ultimate analysis, three different MLP-ANN models were developed. The prediction accuracies of these models were compared statistically to the experimental data. MLP-ANN models have been shown to … |
| Anahtar Kelimeler |
| Higher heating value | Biomass fuels | Proximate analysis | Ultimate analysis | MLP-ANN |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 5 |
| Google Scholar | 8 |