Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods

Sayiter Yıldız; Can Bülent Karakuş

doi:10.17776/csj.897185

EN

Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods

Abstract

The aim of this study is to estimate of organic matter values based on chlorine and turbidity values with the help of ANN and multiple regression (MR) methods. Three different models were done with ANN, and the statistical performance of these models was evaluated with statistical parameters like; µ, SE, σ, R2, RMSE and MAPE. The R2 value of the selected best model was found to be quite high with 0.94. The relationship between the evaluation results of the ANN model and the empirical data (R2 = 0.92) showed that the model was quite successful. In the MR analysis, R2 was determined as 0.63, and a middling significant (p <0.05) relationship was found. Since the calculated F value was greater than the tabulated F value, it was concluded that there is a clear relationship between dependent and independent variables. In addition, spatial distribution maps of chlorine, turbidity, organic matter values were created with the help of the GIS. With these maps, the estimated distribution of the measured parameters in the whole city network was accomplished. This study revealed that turbidity and chlorine parameters are related to organic matter value, and by establishing this relationship, organic matter can be estimated by ANN.

Keywords

Drinking water network, organic matter, Artificial neural network, Multiple regression methods

References

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Details

Primary Language

English

Subjects

Statistics

Journal Section

Research Article

Authors

Sayiter Yıldız ^*
0000-0002-3382-2487
Türkiye

Can Bülent Karakuş
0000-0002-7373-9960
Türkiye

Publication Date

June 30, 2021

Submission Date

March 15, 2021

Acceptance Date

June 4, 2021

Published in Issue

Year 2021 Volume: 42 Number: 2

DOI

https://doi.org/10.17776/csj.897185

IZ

https://izlik.org/JA94CJ46WH

APA

Yıldız, S., & Karakuş, C. B. (2021). Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods. Cumhuriyet Science Journal, 42(2), 441-451. https://doi.org/10.17776/csj.897185

AMA

1.Yıldız S, Karakuş CB. Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods. CSJ. 2021;42(2):441-451. doi:10.17776/csj.897185

Chicago

Yıldız, Sayiter, and Can Bülent Karakuş. 2021. “Estimation of Organic Matter Dependent on Different Variables in Drinking Water Network Using Artificial Neural Network and Multiple Regression Methods”. Cumhuriyet Science Journal 42 (2): 441-51. https://doi.org/10.17776/csj.897185.

EndNote

Yıldız S, Karakuş CB (June 1, 2021) Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods. Cumhuriyet Science Journal 42 2 441–451.

IEEE

[1]S. Yıldız and C. B. Karakuş, “Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods”, CSJ, vol. 42, no. 2, pp. 441–451, June 2021, doi: 10.17776/csj.897185.

ISNAD

Yıldız, Sayiter - Karakuş, Can Bülent. “Estimation of Organic Matter Dependent on Different Variables in Drinking Water Network Using Artificial Neural Network and Multiple Regression Methods”. Cumhuriyet Science Journal 42/2 (June 1, 2021): 441-451. https://doi.org/10.17776/csj.897185.

JAMA

1.Yıldız S, Karakuş CB. Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods. CSJ. 2021;42:441–451.

MLA

Yıldız, Sayiter, and Can Bülent Karakuş. “Estimation of Organic Matter Dependent on Different Variables in Drinking Water Network Using Artificial Neural Network and Multiple Regression Methods”. Cumhuriyet Science Journal, vol. 42, no. 2, June 2021, pp. 441-5, doi:10.17776/csj.897185.

Vancouver

1.Sayiter Yıldız, Can Bülent Karakuş. Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods. CSJ. 2021 Jun. 1;42(2):441-5. doi:10.17776/csj.897185

As of 2026, Cumhuriyet Science Journal will be published in six issues per year, released in February, April, June, August, October, and December

Abstract

Estimation of organic matter dependent on different variables in drinking water network using artificial neural network and multiple regression methods

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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