ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process
Само за регистроване кориснике
2016
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
This article presents the results of nonlinear statistical modeling of the decomposition process of sodium aluminate solution, as part of the Bayer technology for the production of alumina. Based on the data collected in 2011 and 2012 from industrial production in the Biracˇ Alumina Factory, Zvornik (Bosnia and Herzegovina), nonlinear statistical modeling of the industrial processes was
derived. The model was developed as an attempt to define the dependence of the degree of decomposition of sodium aluminate solution as a function of the input parameters of the leaching process: caustic ratio (ak) of the solution; ratio of the crystallization; content of Na2O(caustic) in the solution; the initial temperature of the solution; the final temperature of the solution; average
diameter of the crystallized seeds; and duration of the crystallization process. As a tool for statistical modeling, Adaptive Network Based Fuzzy Inference System (ANFIS) was applied. The defined model using ANFIS met...hodology expressed a high level of fitting, and could be used to effectively predict the degree of decomposition of the sodium aluminate solution as a function of
the input process under industrial conditions.
Кључне речи:
Al(OH)3 / ANFIS / ; Bayer process / DecompositionИзвор:
CHEMICAL ENGINEERING COMMUNICATIONS, 2016, 203, 8, 1053-1061Издавач:
- Taylor & Francis Ltd
Институција/група
Mašinski fakultetTY - JOUR AU - Savić, Marija AU - Mihajlović, Ivan AU - Đorđević, Predrag AU - Živković, Živan PY - 2016 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5002 AB - This article presents the results of nonlinear statistical modeling of the decomposition process of sodium aluminate solution, as part of the Bayer technology for the production of alumina. Based on the data collected in 2011 and 2012 from industrial production in the Biracˇ Alumina Factory, Zvornik (Bosnia and Herzegovina), nonlinear statistical modeling of the industrial processes was derived. The model was developed as an attempt to define the dependence of the degree of decomposition of sodium aluminate solution as a function of the input parameters of the leaching process: caustic ratio (ak) of the solution; ratio of the crystallization; content of Na2O(caustic) in the solution; the initial temperature of the solution; the final temperature of the solution; average diameter of the crystallized seeds; and duration of the crystallization process. As a tool for statistical modeling, Adaptive Network Based Fuzzy Inference System (ANFIS) was applied. The defined model using ANFIS methodology expressed a high level of fitting, and could be used to effectively predict the degree of decomposition of the sodium aluminate solution as a function of the input process under industrial conditions. PB - Taylor & Francis Ltd T2 - CHEMICAL ENGINEERING COMMUNICATIONS T1 - ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process EP - 1061 IS - 8 SP - 1053 VL - 203 DO - 10.1080/00986445.2015.1136292 ER -
@article{ author = "Savić, Marija and Mihajlović, Ivan and Đorđević, Predrag and Živković, Živan", year = "2016", abstract = "This article presents the results of nonlinear statistical modeling of the decomposition process of sodium aluminate solution, as part of the Bayer technology for the production of alumina. Based on the data collected in 2011 and 2012 from industrial production in the Biracˇ Alumina Factory, Zvornik (Bosnia and Herzegovina), nonlinear statistical modeling of the industrial processes was derived. The model was developed as an attempt to define the dependence of the degree of decomposition of sodium aluminate solution as a function of the input parameters of the leaching process: caustic ratio (ak) of the solution; ratio of the crystallization; content of Na2O(caustic) in the solution; the initial temperature of the solution; the final temperature of the solution; average diameter of the crystallized seeds; and duration of the crystallization process. As a tool for statistical modeling, Adaptive Network Based Fuzzy Inference System (ANFIS) was applied. The defined model using ANFIS methodology expressed a high level of fitting, and could be used to effectively predict the degree of decomposition of the sodium aluminate solution as a function of the input process under industrial conditions.", publisher = "Taylor & Francis Ltd", journal = "CHEMICAL ENGINEERING COMMUNICATIONS", title = "ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process", pages = "1061-1053", number = "8", volume = "203", doi = "10.1080/00986445.2015.1136292" }
Savić, M., Mihajlović, I., Đorđević, P.,& Živković, Ž.. (2016). ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process. in CHEMICAL ENGINEERING COMMUNICATIONS Taylor & Francis Ltd., 203(8), 1053-1061. https://doi.org/10.1080/00986445.2015.1136292
Savić M, Mihajlović I, Đorđević P, Živković Ž. ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process. in CHEMICAL ENGINEERING COMMUNICATIONS. 2016;203(8):1053-1061. doi:10.1080/00986445.2015.1136292 .
Savić, Marija, Mihajlović, Ivan, Đorđević, Predrag, Živković, Živan, "ANFIS-Based Prediction of the Decomposition of Sodium Aluminate Solutions in the Bayer Process" in CHEMICAL ENGINEERING COMMUNICATIONS, 203, no. 8 (2016):1053-1061, https://doi.org/10.1080/00986445.2015.1136292 . .