Modeling Drying Process Parameters for Petroleum Drilling Sludge with ANN and ANFIS

Basit Öğe Kaydı
dc.contributor.authorMoralar, Aytac
dc.date.accessioned2024-10-29T17:59:26Z
dc.date.available2024-10-29T17:59:26Z
dc.date.issued2024
dc.departmentTekirdağ Namık Kemal Üniversitesien_US
dc.description.abstractPetroleum drilling sludge (PDS) is one of the most significant waste products generated during drilling activities worldwide. The disposal of this waste must be carried out using the most cost-effective methods available. The objective of this manuscript is to mathematically model the parameters of drying processes experimentally applied to PDS. For this purpose, this study employed two different artificial intelligence techniques: artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs). These methods were used to predict the parameters. In the calculations, the inputs included petroleum drilling mud with varying quantities (50 g, 100 g, and 150 g) and drying times, using a 120 W microwave drying power. The results indicated that the coefficient of determination (R2) and the root mean square error (RMSE) obtained during the test phase for ANFIS were 0.999965 and 0.005425, respectively, while for ANN, the R2 and RMSE were 0.999973 and 0.004774, respectively. Analysis of the evaluation results revealed that both methods provided predictions for moisture content that were closer to experimental values compared to drying rate values.en_US
dc.identifier.doi10.3390/pr12091948
dc.identifier.issn2227-9717
dc.identifier.issue9en_US
dc.identifier.scopus2-s2.0-85205224170en_US
dc.identifier.urihttps://doi.org/10.3390/pr12091948
dc.identifier.urihttps://hdl.handle.net/20.500.11776/14735
dc.identifier.volume12en_US
dc.identifier.wosWOS:001323961400001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofProcessesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectadaptive neuro-fuzzy inference systemsen_US
dc.subjectartificial neural networksen_US
dc.subjectmicrowave dryingen_US
dc.subjectdrilling sludgeen_US
dc.titleModeling Drying Process Parameters for Petroleum Drilling Sludge with ANN and ANFISen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu