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Paper Information

Journal:   JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ)   FALL 2008 , Volume 36 , Number 2 (54) MECHANICAL ENGINEERING; Page(s) 81 To 86.
 
Paper: 

DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS

 
 
Author(s):  FARZI A., MEHRABANI ARJMAND, BOZORGMEHRY BOOZARJOMEHRY RAMIN
 
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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.
 
Keyword(s): NONLINEAR DYNAMIC DATA RECONCILIATION, ARTIFICIAL NEURAL NETWORKS, DISTILLATION COULMN, DYNAMIC SIMULATION.
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

FARZI, A., & MEHRABANI, A., & BOZORGMEHRY BOOZARJOMEHRY, R. (2008). DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), 36(2 (54) MECHANICAL ENGINEERING), 81-86. https://www.sid.ir/en/journal/ViewPaper.aspx?id=277257



Vancouver: Copy

FARZI A., MEHRABANI ARJMAND, BOZORGMEHRY BOOZARJOMEHRY RAMIN. DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ). 2008 [cited 2021July23];36(2 (54) MECHANICAL ENGINEERING):81-86. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=277257



IEEE: Copy

FARZI, A., MEHRABANI, A., BOZORGMEHRY BOOZARJOMEHRY, R., 2008. DATA RECONCILIATION BY USING ARTIFICIAL NEURAL NETWORKS. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TABRIZ), [online] 36(2 (54) MECHANICAL ENGINEERING), pp.81-86. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=277257.



 
 
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