DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS

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FARZI A.; MEHRABANI ARJMAND; BOZORGMEHRY BOOZARJOMEHRY RAMIN

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Journal: JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ) Year:2008 | Volume:36 | Issue:2 (54) MECHANICAL ENGINEERING Page(s): 81-86

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Information Journal Paper

Title

DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS

Author(s)

FARZI A. | MEHRABANI ARJMAND | BOZORGMEHRY BOOZARJOMEHRY RAMIN | Issue Writer Certificate

Keywords

NONLINEAR DYNAMIC DATA RECONCILIATIONQ1

ARTIFICIAL NEURAL NETWORKSQ1

DISTILLATION COULMNQ1

DYNAMIC SIMULATION.Q1

Abstract

Artificial Neural Networks (ANNs) with advantages such as learning and estimation capabilities are widely used in various fields of chemical engineering such as process simulation and control. They are suitable for modeling, simulation, and solution of highly nonlinear problems. One of these problems is NONLINEAR DYNAMIC DATA RECONCILIATION. In this paper a new method, namely NetDDR, which uses ANNs, is described. NDDR of a distillation column is used to illustrate different aspects and advantages of the new method.

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APA: Copy

FARZI, A., MEHRABANI, ARJMAND, & BOZORGMEHRY BOOZARJOMEHRY, RAMIN. (2008). DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), 36(2 (54) MECHANICAL ENGINEERING), 81-86. SID. https://sid.ir/paper/43715/en

Vancouver: Copy

FARZI A., MEHRABANI ARJMAND, BOZORGMEHRY BOOZARJOMEHRY RAMIN. DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ)[Internet]. 2008;36(2 (54) MECHANICAL ENGINEERING):81-86. Available from: https://sid.ir/paper/43715/en

IEEE: Copy

A. FARZI, ARJMAND MEHRABANI, and RAMIN BOZORGMEHRY BOOZARJOMEHRY, “DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS,” JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), vol. 36, no. 2 (54) MECHANICAL ENGINEERING, pp. 81–86, 2008, [Online]. Available: https://sid.ir/paper/43715/en

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