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

Abstract

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 qe 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.

Analysis of the performance of a crude-oil desalting system based on historical data

“…As such, the development of an interpretive model should also consider the possibility of including information about (i) the specific desalting module from which each measurement is collected and (ii) the type of demulsifiers used for a given record. We take this type of information into account in our regression models by following a strategy proposed in prior studies (e.g., [37]) and mapping information on the location of data sampling and the type of employed demulsifiers into a set dummy (categorical) variables collected, respectively, in vectors U and Q. We set U 1 = 1 (while U 2 = U 3 = 0) when a measurement record is collected in the first desalting units, corresponding notations being employed to identify data sampled at the second or third desalting units.…”

A review on the porous geopolymer preparation for structural and functional materials applications

“…Adsorption of metal ions with different pore‐forming methods 13,23,60,71,72,90,108,110,111,115,132,140,146,153,210,218–234 …”

“…Different sizes of geopolymers were obtained by ball milling. Beniz et al 222 . found that the smaller the particle size of geopolymer is, the higher the surface activity and the better adsorption performance are.…”

Quantitative Analysis of a Weak Correlation between Complicated Data on the Basis of Principal Component Analysis

“…Using the processing of heavy metal adsorption as an example, Bingöl et al proposed a nonlinear autoregressive network with exogenous inputs (NARX) and compared with multiple regression analysis (MLR). It was found that the prediction ability of the NARX method was superior to the MLR method using dummy variables, which can successfully achieve the evaluation of the adsorption process on the experimental data [ 30 ]. Canonical correlation analysis (CCA) can be used to study the correlation between two datasets, which is a classical statistical tool to correlate multivariate data.…”