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

Petroleum 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...

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Veröffentlicht in:	Processes 2024-09, Vol.12 (9), p.1948
1. Verfasser:	Moralar, Aytaç
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive systems Analysis Artificial intelligence Artificial neural networks Drilling Drilling muds Drying Energy consumption Energy efficiency Fuzzy logic Fuzzy systems Machine learning Moisture content Neural networks Oil and gas exploration Oil well drilling Petroleum Petroleum industry Petroleum mining Process controls Process parameters Root-mean-square errors Sludge Sludge drying Water content
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