Estimation of xanthate decomposition percentage as a function of pH, temperature, and time by least squares regression and adaptive neurofuzzy inference system

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BEHNAMFARD ALI; Veglio Francesco

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Journal Paper

Paper Information

Journal: International Journal of Mining and Geo-Engineering Year:2019 | Volume:53 | Issue:2 Page(s): 157-163

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Title

Estimation of xanthate decomposition percentage as a function of pH, temperature, and time by least squares regression and adaptive neurofuzzy inference system

Author(s)

BEHNAMFARD ALI | Veglio Francesco | Issue Writer Certificate

Keywords

Xanthate

Decomposition percentage

Estimation

ANFIS

Regression

Abstract

Estimating the Xanthate Decomposition percentage has a crucial role in the treatment of Xanthate contaminated wastewaters and in the improvement of the flotation process performance. In this research, the modeling of Xanthate Decomposition percentage was performed using the least squares Regression method and the Adaptive Neuro-Fuzzy Inference System (ANFIS). A multi-variable Regression equation and the ANFIS models with various types and numbers of membership functions (MFs) were constructed, trained, and tested for the Estimation of Xanthate Decomposition percentage. The statistical indices such as Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R2) were used to evaluate the performance of various models. The lowest values of RMSE and MAPE and the closest value of R2 to unity were determined for the ANFIS model with the triangular membership function and the number of input MFs 9 9 9 (0. 766906, 3. 553509 and 0. 998793). This indicates that ANFIS is a powerful method in the Estimation of Xanthate Decomposition percentage. The performance of new-adopted ANFIS data modeling was significantly better than the conventional least squares Regression method.

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APA: Copy

BEHNAMFARD, ALI, & Veglio, Francesco. (2019). Estimation of xanthate decomposition percentage as a function of pH, temperature, and time by least squares regression and adaptive neurofuzzy inference system. INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING, 53(2), 157-163. SID. https://sid.ir/paper/330035/en

Vancouver: Copy

BEHNAMFARD ALI, Veglio Francesco. Estimation of xanthate decomposition percentage as a function of pH, temperature, and time by least squares regression and adaptive neurofuzzy inference system. INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING[Internet]. 2019;53(2):157-163. Available from: https://sid.ir/paper/330035/en

IEEE: Copy

ALI BEHNAMFARD, and Francesco Veglio, “Estimation of xanthate decomposition percentage as a function of pH, temperature, and time by least squares regression and adaptive neurofuzzy inference system,” INTERNATIONAL JOURNAL OF MINING AND GEO-ENGINEERING, vol. 53, no. 2, pp. 157–163, 2019, [Online]. Available: https://sid.ir/paper/330035/en

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