Comparison of multiple regression analysis using dummy variables and a NARX network model: an example of a heavy metal adsorption process

Bingöl D., Xiyili H., Elevli S., Kilic E., Çetintaş S.

WATER AND ENVIRONMENT JOURNAL, cilt.32, ss.186-196, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1111/wej.12314
  • Dergi Adı: WATER AND ENVIRONMENT JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.186-196
  • Anahtar Kelimeler: fly ash, heavy metals, mechanical activation, MLR, NARX model, FLY-ASH, AQUEOUS-SOLUTION, NEURAL-NETWORK, WASTE-WATER, REMOVAL, DYES, OPTIMIZATION, PREDICTION, IONS
  • Kocaeli Üniversitesi Adresli: Evet

Özet

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.