Frictional Pressure Drop Prediction Using ANN for Gas-Non-Newtonian Liquid Flow through 45° Bend
Abstract
Keywords
Full Text:
PDFReferences
D. M. Himmelblau, “Application of artificial neural network in chemical engineering,” Korean J. Chem. Engg., vol. 17, 2000, pp 373 – 392.
S. K. Das, Studies on two-phase gas-non-Newtonian liquid flow in horizontal, vertical tubes and bends, Ph.D. Thesis, Indian Institute of Technology, Kharagpur, 1988.
K. Yetilmezsoy and S. Demirel, “Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous by Antep pistachio (Pistacia Vera L.) shells,” J. Haz. Mat., vol 153, 2008, pp 1288 – 1300.
J. Sola and J. Sevilla, “Importance of input data normalization for the application of neural networks to complex industrial problems,” IEEE Trans. Nuclear Sci., vol 44(3), 1997, pp 1464 – 1468.
Guan-De Wu and Shang-Lien Lo, “Effects of data normalization and inherent-factor on decision of optimal coagulant dosage in water treatment by artificial neural network,” Expert Systems with App., vol 37(7), 2010, pp 4974 – 4983.
Refbacks
- There are currently no refbacks.