Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process
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This paper presents the results of statistical modeling of the bauxite leaching process, as part of Bayer technology for an alumina production. Based on the data, collected during the period between 2008 - 2009 (659 days) from the industrial production in the alumina factory Birač, Zvornik (Bosnia and Herzegovina), the statistical modeling of the above mentioned process was performed. The dependant variable, which was the main target of the modeling procedure, was the degree of Al2O3 recovery from boehmite bauxite during the leaching process. The statistical model was developed as an attempt to define the dependence of the Al2O3 degree of recovery as a function of input variables of the leaching process: composition of bauxite, composition of the sodium aluminate solution and the caustic module of the solution before and after the leaching process. As the statistical modeling tools, Multiple Linear Regression Analysis (MLRA) and Artificial Neural Networks (ANNs) were used. The fitting ...level, obtained by using the MLRA, was R2 = 0.463, while ANN resulted with the value of R2 = 0.723. This way, the model, defined by using the ANN methodology, can be used for the efficient prediction of the Al2O3 degree of recovery as a function of the process inputs, under the industrial conditions of the alumina factory Birač, Zvornik. The proposed model also has got a universal character and, as such, is applicable in other factories practicing the Bayer technology for alumina production.
Кључне речи:
leaching / bauxite / Bayer process / statistical modeling / neural networksИзвор:
JOURNAL OF THE SERBIAN CHEMICAL SOCIETY, 2012, 77, 9, 1259-1271Издавач:
- Serbian Chemical Society
Институција/група
Mašinski fakultetTY - JOUR AU - Đurić, Isidora AU - Mihajlović, Ivan AU - Živković, Živan AU - Kešelj, Dragana PY - 2012 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5453 AB - This paper presents the results of statistical modeling of the bauxite leaching process, as part of Bayer technology for an alumina production. Based on the data, collected during the period between 2008 - 2009 (659 days) from the industrial production in the alumina factory Birač, Zvornik (Bosnia and Herzegovina), the statistical modeling of the above mentioned process was performed. The dependant variable, which was the main target of the modeling procedure, was the degree of Al2O3 recovery from boehmite bauxite during the leaching process. The statistical model was developed as an attempt to define the dependence of the Al2O3 degree of recovery as a function of input variables of the leaching process: composition of bauxite, composition of the sodium aluminate solution and the caustic module of the solution before and after the leaching process. As the statistical modeling tools, Multiple Linear Regression Analysis (MLRA) and Artificial Neural Networks (ANNs) were used. The fitting level, obtained by using the MLRA, was R2 = 0.463, while ANN resulted with the value of R2 = 0.723. This way, the model, defined by using the ANN methodology, can be used for the efficient prediction of the Al2O3 degree of recovery as a function of the process inputs, under the industrial conditions of the alumina factory Birač, Zvornik. The proposed model also has got a universal character and, as such, is applicable in other factories practicing the Bayer technology for alumina production. PB - Serbian Chemical Society T2 - JOURNAL OF THE SERBIAN CHEMICAL SOCIETY T1 - Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process EP - 1271 IS - 9 SP - 1259 VL - 77 DO - 10.2298/JSC110526193D ER -
@article{ author = "Đurić, Isidora and Mihajlović, Ivan and Živković, Živan and Kešelj, Dragana", year = "2012", abstract = "This paper presents the results of statistical modeling of the bauxite leaching process, as part of Bayer technology for an alumina production. Based on the data, collected during the period between 2008 - 2009 (659 days) from the industrial production in the alumina factory Birač, Zvornik (Bosnia and Herzegovina), the statistical modeling of the above mentioned process was performed. The dependant variable, which was the main target of the modeling procedure, was the degree of Al2O3 recovery from boehmite bauxite during the leaching process. The statistical model was developed as an attempt to define the dependence of the Al2O3 degree of recovery as a function of input variables of the leaching process: composition of bauxite, composition of the sodium aluminate solution and the caustic module of the solution before and after the leaching process. As the statistical modeling tools, Multiple Linear Regression Analysis (MLRA) and Artificial Neural Networks (ANNs) were used. The fitting level, obtained by using the MLRA, was R2 = 0.463, while ANN resulted with the value of R2 = 0.723. This way, the model, defined by using the ANN methodology, can be used for the efficient prediction of the Al2O3 degree of recovery as a function of the process inputs, under the industrial conditions of the alumina factory Birač, Zvornik. The proposed model also has got a universal character and, as such, is applicable in other factories practicing the Bayer technology for alumina production.", publisher = "Serbian Chemical Society", journal = "JOURNAL OF THE SERBIAN CHEMICAL SOCIETY", title = "Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process", pages = "1271-1259", number = "9", volume = "77", doi = "10.2298/JSC110526193D" }
Đurić, I., Mihajlović, I., Živković, Ž.,& Kešelj, D.. (2012). Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process. in JOURNAL OF THE SERBIAN CHEMICAL SOCIETY Serbian Chemical Society., 77(9), 1259-1271. https://doi.org/10.2298/JSC110526193D
Đurić I, Mihajlović I, Živković Ž, Kešelj D. Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process. in JOURNAL OF THE SERBIAN CHEMICAL SOCIETY. 2012;77(9):1259-1271. doi:10.2298/JSC110526193D .
Đurić, Isidora, Mihajlović, Ivan, Živković, Živan, Kešelj, Dragana, "Artificial neural network prediction of aluminum extraction from bauxite in the Bayer process" in JOURNAL OF THE SERBIAN CHEMICAL SOCIETY, 77, no. 9 (2012):1259-1271, https://doi.org/10.2298/JSC110526193D . .