PREDICTION OF RED MUD BOUND-SODA LOSSES IN BAYER PROCESS USING NEURAL NETWORKS

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MAHMOUDIAN M.; GHAEMI A.; HASHEMABADI H.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF CHEMICAL ENGINEERING Year:2016 | Volume:13 | Issue:2 Page(s): 46-56

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Title

PREDICTION OF RED MUD BOUND-SODA LOSSES IN BAYER PROCESS USING NEURAL NETWORKS

Author(s)

MAHMOUDIAN M. | GHAEMI A. | HASHEMABADI H. | Issue Writer Certificate

Keywords

NEURAL NETWORK

LINEAR REGRESSION

BOUND-SODA

RED MUD

BAYER PROCESS

Abstract

In the BAYER PROCESS, the reaction of silica in bauxite with caustic soda causes the loss of a great amount of NaOH. In this research, the BOUND-SODA losses in Iran Alumina Complex solid residue (red mud) are predicted using intelligent techniques. This method, based on the application of regression and artificial NEURAL NETWORKs (AAN), has been used to predict RED MUD BOUND-SODA losses in Iran Alumina Company. Multilayer perceptron (MLP), radial basis function (RBF) networks and multiple LINEAR REGRESSIONs (MLR) were applied. The results of three methodologies were compared for their predictive capabilities in terms of the correlation coefficient (R), mean square error (MSE) and the absolute average deviation (AAD) based on the experimental data set. The optimum MLP network was obtained with structure of two hidden layers including 13 and 15 neurons in each layer respectively. The results showed that the RBF model with 0.117, 5.909 and 0.82 in MSE, AAD and R, respectively, is extremely accurate in prediction as compared with MLP and MLR.

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APA: Copy

MAHMOUDIAN, M., GHAEMI, A., & HASHEMABADI, H.. (2016). PREDICTION OF RED MUD BOUND-SODA LOSSES IN BAYER PROCESS USING NEURAL NETWORKS. IRANIAN JOURNAL OF CHEMICAL ENGINEERING, 13(2), 46-56. SID. https://sid.ir/paper/298469/en

Vancouver: Copy

MAHMOUDIAN M., GHAEMI A., HASHEMABADI H.. PREDICTION OF RED MUD BOUND-SODA LOSSES IN BAYER PROCESS USING NEURAL NETWORKS. IRANIAN JOURNAL OF CHEMICAL ENGINEERING[Internet]. 2016;13(2):46-56. Available from: https://sid.ir/paper/298469/en

IEEE: Copy

M. MAHMOUDIAN, A. GHAEMI, and H. HASHEMABADI, “PREDICTION OF RED MUD BOUND-SODA LOSSES IN BAYER PROCESS USING NEURAL NETWORKS,” IRANIAN JOURNAL OF CHEMICAL ENGINEERING, vol. 13, no. 2, pp. 46–56, 2016, [Online]. Available: https://sid.ir/paper/298469/en

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