Preprints
https://doi.org/10.5194/dwes-2021-8
https://doi.org/10.5194/dwes-2021-8
31 Mar 2021
 | 31 Mar 2021
Status: this preprint has been withdrawn by the authors.

Predicting turbidity and Aluminum in drinking water treatment plants using Hybrid Network (GA- ANN) and GEP

Ruba Alsaeed, Bassam Alaji, and Mazen Ebrahim

Abstract. Turbidity is the most important parameter needed to check the status of drinking water, as it is an integrated parameter because its high values indicate high values of other parameters related to water quality. Coagulation and flocculation are the most essential processes for the removal of turbidity in drinking water treatment plants. Using alum coagulants increases the aluminum residuals in treated water, which have been linked to Alzheimer's disease pathogenesis.

In this paper, a hybrid algorithm (GA-ANN) used to predict the turbidity values in the drinking water purification plant in Al Qusayr was used.

The models were constructed using raw water data: turbidity of raw water, pH, conductivity, temperature, and coagulant dose, to predict the turbidity values coming out of the plant.

Several models built and fitness detected for each model, the network with the highest fitness was selected, and then a hybrid prediction network was constructed.

The selected network was the most able to predict turbidity of the outlet with high accuracy with a correlation coefficient (0. 9940) and a root mean square error of 0.1078.

And 4 equations for determining the value of the residual aluminum was obtained using Gene expression method, and the best equation produced results with very good accuracy, in this regard it can be referred to RMSE = 0.02 R = 0.9 for the best model.

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Ruba Alsaeed, Bassam Alaji, and Mazen Ebrahim

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on dwes-2021-8', fadi Asker, 02 Apr 2021
    • AC1: 'Reply on CC1', Ruba Alsaeed, 02 Apr 2021
  • CC2: 'Comment on dwes-2021-8', Salim Heddam, 03 Apr 2021
    • AC3: 'Reply on CC2', Ruba Alsaeed, 12 Apr 2021
    • AC4: 'Reply on CC2', Ruba Alsaeed, 12 Apr 2021
  • CC3: 'Comment on dwes-2021-8', Lina khouri, 04 Apr 2021
    • AC2: 'Reply on CC3', Ruba Alsaeed, 07 Apr 2021
  • CC4: 'Comment on dwes-2021-8', Lilas Nabhan, 12 Apr 2021
    • AC5: 'Reply on CC4', Ruba Alsaeed, 14 Apr 2021
  • CC5: 'Comment on dwes-2021-8', amin hasanalipou shahrabadi, 13 Apr 2021
    • AC6: 'Reply on CC5', Ruba Alsaeed, 14 Apr 2021
  • CC6: 'Comment on dwes-2021-8', Lina khouri, 14 Apr 2021
  • CC7: 'Comment on dwes-2021-8', Prakash Jagadeesan, 30 Apr 2021
  • CC8: 'Comment on dwes-2021-8', Adnan Sallom, 30 Apr 2021
    • CC10: 'Reply on CC8', Ruba Alsaeed, 09 May 2021
    • AC7: 'Reply on CC8', Ruba Alsaeed, 09 May 2021
  • CC9: 'Comment on dwes-2021-8', Rana Muhammad Adnan Ikram, 02 May 2021
  • RC1: 'Comment on dwes-2021-8', Sina Moharramzadeh, 24 Jun 2021
    • AC8: 'Reply on RC1', Ruba Alsaeed, 02 Jul 2021
      • RC2: 'Reply on AC8', Sina Moharramzadeh, 25 Jul 2021
        • AC10: 'Reply on RC2', Ruba Alsaeed, 19 Aug 2021
  • RC3: 'Comment on dwes-2021-8', Anonymous Referee #2, 09 Aug 2021
    • AC9: 'Reply on RC3', Ruba Alsaeed, 19 Aug 2021

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on dwes-2021-8', fadi Asker, 02 Apr 2021
    • AC1: 'Reply on CC1', Ruba Alsaeed, 02 Apr 2021
  • CC2: 'Comment on dwes-2021-8', Salim Heddam, 03 Apr 2021
    • AC3: 'Reply on CC2', Ruba Alsaeed, 12 Apr 2021
    • AC4: 'Reply on CC2', Ruba Alsaeed, 12 Apr 2021
  • CC3: 'Comment on dwes-2021-8', Lina khouri, 04 Apr 2021
    • AC2: 'Reply on CC3', Ruba Alsaeed, 07 Apr 2021
  • CC4: 'Comment on dwes-2021-8', Lilas Nabhan, 12 Apr 2021
    • AC5: 'Reply on CC4', Ruba Alsaeed, 14 Apr 2021
  • CC5: 'Comment on dwes-2021-8', amin hasanalipou shahrabadi, 13 Apr 2021
    • AC6: 'Reply on CC5', Ruba Alsaeed, 14 Apr 2021
  • CC6: 'Comment on dwes-2021-8', Lina khouri, 14 Apr 2021
  • CC7: 'Comment on dwes-2021-8', Prakash Jagadeesan, 30 Apr 2021
  • CC8: 'Comment on dwes-2021-8', Adnan Sallom, 30 Apr 2021
    • CC10: 'Reply on CC8', Ruba Alsaeed, 09 May 2021
    • AC7: 'Reply on CC8', Ruba Alsaeed, 09 May 2021
  • CC9: 'Comment on dwes-2021-8', Rana Muhammad Adnan Ikram, 02 May 2021
  • RC1: 'Comment on dwes-2021-8', Sina Moharramzadeh, 24 Jun 2021
    • AC8: 'Reply on RC1', Ruba Alsaeed, 02 Jul 2021
      • RC2: 'Reply on AC8', Sina Moharramzadeh, 25 Jul 2021
        • AC10: 'Reply on RC2', Ruba Alsaeed, 19 Aug 2021
  • RC3: 'Comment on dwes-2021-8', Anonymous Referee #2, 09 Aug 2021
    • AC9: 'Reply on RC3', Ruba Alsaeed, 19 Aug 2021
Ruba Alsaeed, Bassam Alaji, and Mazen Ebrahim
Ruba Alsaeed, Bassam Alaji, and Mazen Ebrahim

Viewed

Total article views: 2,425 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,280 1,058 87 2,425 51 36
  • HTML: 1,280
  • PDF: 1,058
  • XML: 87
  • Total: 2,425
  • BibTeX: 51
  • EndNote: 36
Views and downloads (calculated since 31 Mar 2021)
Cumulative views and downloads (calculated since 31 Mar 2021)

Viewed (geographical distribution)

Total article views: 2,237 (including HTML, PDF, and XML) Thereof 2,237 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jul 2024
Download

This preprint has been withdrawn.

Short summary
A hybrid algorithm (GA-ANN) was used to predict the turbidity values in the drinking water plant in Al Qusayr. Several models built and fitness detected for each, the network with the highest fitness selected, then the network was constructed. The network was able to predict turbidity with high accuracy, R (0. 9940) and a RMSE of 0.1078. And 4 equations for determining the value of the residual aluminum was obtained using Gene expression, the best equation results were, RMSE = 0.02, R = 0.9.