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Comparison of multiple regression analysis using dummy variables and a NARX network model: an example of a heavy metal adsorption process
Author(s) -
Bingöl Deniz,
Xiyili Haibibu,
Elevli Sermin,
Kılıç Erdal,
Çetintaş Seda
Publication year - 2018
Publication title -
water and environment journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 37
eISSN - 1747-6593
pISSN - 1747-6585
DOI - 10.1111/wej.12314
Subject(s) - fly ash , adsorption , nonlinear autoregressive exogenous model , process engineering , regression analysis , process (computing) , coal , linear regression , autoregressive model , chemistry , environmental science , biological system , mathematics , waste management , computer science , statistics , engineering , organic chemistry , operating system , biology
In the present study, the adsorption characteristics of coal fly ash obtained from the Kangal Power Plant, Turkey and activated fly ash in the planetary ball mill were investigated to remove the heavy metal ions from aqueous solutions. The adsorption capacity was compared for the first time using a multiple regression analysis with dummy variables and a non‐linear auto regressive exogenous (NARX) network model. An equation was obtained for all types of adsorbents or heavy metals using the regression of q e on the dummy variables. The predictive ability of NARX was found to be better than that of multiple regression using dummy variables. These models can also be successfully implemented on the experimental data to evaluate the adsorption process. In addition, fly ash is a low cost alternative since it is a more economical and environmentally friendly adsorbent and it is abundant in both nature and from waste material from industry.