Articles | Volume 11, issue 1
https://doi.org/10.5194/dwes-11-1-2018
https://doi.org/10.5194/dwes-11-1-2018
Research article
 | 
29 Jan 2018
Research article |  | 29 Jan 2018

Optimum coagulant forecasting by modeling jar test experiments using ANNs

Sadaf Haghiri, Amin Daghighi, and Sina Moharramzadeh

Viewed

Total article views: 7,471 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,563 2,758 150 7,471 146 214
  • HTML: 4,563
  • PDF: 2,758
  • XML: 150
  • Total: 7,471
  • BibTeX: 146
  • EndNote: 214
Views and downloads (calculated since 05 Sep 2017)
Cumulative views and downloads (calculated since 05 Sep 2017)

Viewed (geographical distribution)

Total article views: 7,471 (including HTML, PDF, and XML) Thereof 6,652 with geography defined and 819 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Jan 2026
Download
Short summary
Modeling can be used to overcome water jar test limitations. In this research study, MLP-type ANNs with one hidden layer have been used for modeling jar tests to determine the dosage level of coagulant used in water treatment processes. The data contained in this research have been obtained from the drinking water treatment plant located in the Ardabil province in Iran. To evaluate the performance of the model, the mean square error and the correlation coefficient parameters have been used.
Share