Record Details

<strong>Support vector regression: A novel soft computing technique for predicting the removal of cadmium from wastewater</strong>

Online Publishing @ NISCAIR

View Archive Info
 
 
Field Value
 
Authentication Code dc
 
Title Statement <strong>Support vector regression: A novel soft computing technique for predicting the removal of cadmium from wastewater</strong>
 
Added Entry - Uncontrolled Name PARVEEN, NUSRAT ; ALIGARH MUSLIM UNIVERSITY
Zaidi, Sadaf ; Department of Chemical Engineering, Aligarh Muslim University, India
Danish, Mohammad ; Department of Chemical Engineering, Aligarh Muslim University, India
 
Uncontrolled Index Term Heavy metals; Low cost adsorbent; Support vector regression (SVR); Coefficient of determination (R2); Average relative error (AARE)
 
Summary, etc. The presence of toxic heavy metals in the wastewater coming from industries is of great concern across the world. In the present work, a novel soft computing technique support vector regression (SVR)technique has been used to predict the removal of cadmium ions from wastewater with agricultural waste ‘rice polish’ as a low-cost adsorbent, with contact time, initial adsorbate concentration, <em>p</em>H of the medium, and temperature as the independent parameters. The developed SVR-based model has been compared with the widely used multiple regression (MR) model based on the statistical parameters such as coefficient of determination (R<sup>2</sup>), average relative error (AARE) etc. The prediction performance of SVR-based model has been found to be more accurate and generalized in comparison to MR model with low AARE values of 0.67% and high R<sup>2 </sup>values of 0.9997 while MR model gives an AARE value of 29.27% and 0.2161 as coefficient of determination (R<sup>2</sup>). Furthermore, it has also been observed that the SVR model effectively predicts the behavior of the complex interaction process of cadmium ions removal from waste water under various experimental conditions.
 
Publication, Distribution, Etc. Indian Journal of Chemical Technology (IJCT)
2020-08-21 12:30:09
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/IJCT/article/view/18954
 
Data Source Entry Indian Journal of Chemical Technology (IJCT); ##issue.vol## 27, ##issue.no## 1 (2020): Indian Journal of Chemical Technology
 
Language Note en
 
Nonspecific Relationship Entry http://op.niscair.res.in/index.php/IJCT/article/download/18954/57663
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57664
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57665
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57666
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57667
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57668
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57669
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57670
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57671
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57672
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57673
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57674
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57675
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57676
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57677
http://op.niscair.res.in/index.php/IJCT/article/download/18954/57678