2019 IEEE International Conference on Innovative Research and Development (ICIRD) 2019
DOI: 10.1109/icird47319.2019.9074747
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Modeling Vertical Roller Mill Raw Meal Residue by Implementing Neural Network

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Cited by 2 publications
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“…Rather than huge expansion, most industries will focus on maximizing resources for maximum pro tability. Consequently, a study of the impact of operational parameters on ball mill energy e ciency revealed a low particle collision energy will be a re ection of coarse particle size observed at the mill outlet ne products (Fernandes, Halim, &Wahab, 2019;Ghalandari & Iranmanesh, 2020;Simmons, Gorby, &Terembula, 2005). Therefore, to achieve a narrow particle size distribution, applying moderate energy to particles is necessary for this type of operation over a period of use (Tsakalakis & Stamboltzis, 2008).…”
Section: Introductionmentioning
confidence: 99%
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“…Rather than huge expansion, most industries will focus on maximizing resources for maximum pro tability. Consequently, a study of the impact of operational parameters on ball mill energy e ciency revealed a low particle collision energy will be a re ection of coarse particle size observed at the mill outlet ne products (Fernandes, Halim, &Wahab, 2019;Ghalandari & Iranmanesh, 2020;Simmons, Gorby, &Terembula, 2005). Therefore, to achieve a narrow particle size distribution, applying moderate energy to particles is necessary for this type of operation over a period of use (Tsakalakis & Stamboltzis, 2008).…”
Section: Introductionmentioning
confidence: 99%
“…According to this study, arti cial intelligence with optimization algorithms were used in order to model the energy e ciency of vertical raw mills. Despite this, ANFIS has been used to optimize enzyme synthesis (Kumar, Singh, Arya, Bhatti, &Sharma, 2018; Uzuner & Çekmecelioğlu, 2016), biogas production prediction (Asadi, Guo, &McPhedran, 2020), air pollutant prediction (Noori, Hoshyaripour, Ashra , &Araabi, 2010; Shamshirband, Hadipoor, Baghban, Mosavi, Bukor, &Várkonyi-Kóczy, 2019), raw meal process exergy e ciency(A. I. Okoji, Anozie, &Omoleye, 2021), biomass prediction using grid partitioning, sub-clustering, and fuzzy cmeans clustering algorithms (Akkaya, 2016), to predict DBP (trihalomethanes) levels in the water treatment plant (C. N. Okoji, Okoji, Ibrahim, &Obinna, 2022) and vertical raw mill product quality (Fernandes et al, 2019), however, we know of no other study that utilizes this model to predict and optimize vertical raw mill energy e ciency in cement processing plants. The focus of this work was to create different models to predict vertical raw mill energy e ciency while taking plant operating data into account in order to avoid the problems of experimental testing.…”
Section: Introductionmentioning
confidence: 99%