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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.1
- 수록면
- 41 - 50 (10page)
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초록· 키워드
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Artificial neural network was used to predict the copper ore flotation indices of Separation Efficiency (SE) and Selectivity Index (SI) within different operational conditions. The aim was to predict SECu and SIFe and SIMo as a function of chemical reagent dosages (collector, frother, modifier), feed rate, solid percentage, and the feed grade of Cu, Fe, and Mo. A three-layered back propagation neural network with the structure of 9-10-10-3 is selected and standard Bayesian regularization was used as a training function in which, it is unnecessary the validation data-set being apart from the training data-set. The advantage of this algorithm is the minimization of weights and linear combinations of squared errors of producing the appropriate network. In the training and testing stages, the quite satisfactory correlation coefficient of 1 for three training outputs and .93, .9, and .88 for testing outputs was achieved. The results show that the proposed approach models can be used to determine the most advantageous industrial conditions for the expected SE and SI in the froth flotation process.
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참고문헌 (30)
참고문헌 신청
Al-Thyabat, S. / 2008 / On the optimization of froth flotation by the use of an artificial neural network / Journal of China University of Mining and Technology 18(3):418~426
Anderson, J. / 1995 / An introduction to neural networks / Prentice-Hall
Anderson, D. / 1992 / Artificial neural networks technology
Asghar Azizi / 2014 / Influence of collector dosage and pulp chemistry on copper flotation / Geosystem Engineering 17(6):311~316
Asghar Azizi / 2015 / A study on the modified flotation parameters and selectivity index in copper flotation / Particulate Science and Technology 35(1):38~44
Anderson, J. / 1995 / An introduction to neural networks / Prentice-Hall
Anderson, D. / 1992 / Artificial neural networks technology
Asghar Azizi / 2014 / Influence of collector dosage and pulp chemistry on copper flotation / Geosystem Engineering 17(6):311~316
Asghar Azizi / 2015 / A study on the modified flotation parameters and selectivity index in copper flotation / Particulate Science and Technology 35(1):38~44
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