Water Quality Classification Based on Minimum Qualitative Parameter (Case Study: Karun River)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

dezfooli donya; mooghari seyed mohammad hossein; EBRAHIMI KUMARS; ARAGHINEJAD SHAHAB

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Natural Environment Year:2017 | Volume:70 | Issue:3 Page(s): 583-595

Download Full-Text

Persian Verion

View:

988

Download:

Cites:

Information Journal Paper

Title

Water Quality Classification Based on Minimum Qualitative Parameter (Case Study: Karun River)

Author(s)

dezfooli donya | mooghari seyed mohammad hossein | EBRAHIMI KUMARS | ARAGHINEJAD SHAHAB | Issue Writer Certificate

Keywords

Surface waterQ2

Water quality parametersQ1

NSFWQIQ1

Water quality classificationQ1

ModelingQ1

Abstract

Rivers are considered one of the most important resources of providing fresh water. Restrictions faced by such resources underline the necessity of preserving their quality. Water quality indices are usually resorted to qualitatively monitor water resources. Any of such indices is calculated with regard to a series of specific qualitative parameters. The process of sampling and quantification of the aforementioned parameters are, however, time-consuming and costly. Finding a reliable method comprised of minimum qualitative parameters could be, therefore, of great help in classifying water quality. As an alternative to the common NSFQWI, the advantages of the Probabilistic Neural Network (PNN) as a classifier are used in the present study to classify water quality of Karun River. In order to fulfill this objective, the qualitative statistics of 172 samples were used in a way that qualitative parameters and water quality classes derived from NSFWQI are used respectively as the input and output of the model. The assessment criteria of error rate, error value, accuracy and Spearman’ s correlation coefficient were used to evaluate the performance of PNN model. The results showed that through making use of merely three parameters of turbidity, fecal coliform and total dissolved solids, PNN model is capable of classifying water quality with the accuracy of 94. 365% and 90. 7769% at two stages of training and test respectively which in turn indicates considerable accuracy of PNN in determining Water quality classification.

Cites

No record.

References

No record.

Cite

APA: Copy

dezfooli, donya, mooghari, seyed mohammad hossein, EBRAHIMI, KUMARS, & ARAGHINEJAD, SHAHAB. (2017). Water Quality Classification Based on Minimum Qualitative Parameter (Case Study: Karun River). JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 70(3 ), 583-595. SID. https://sid.ir/paper/195087/en

Vancouver: Copy

dezfooli donya, mooghari seyed mohammad hossein, EBRAHIMI KUMARS, ARAGHINEJAD SHAHAB. Water Quality Classification Based on Minimum Qualitative Parameter (Case Study: Karun River). JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2017;70(3 ):583-595. Available from: https://sid.ir/paper/195087/en

IEEE: Copy

donya dezfooli, seyed mohammad hossein mooghari, KUMARS EBRAHIMI, and SHAHAB ARAGHINEJAD, “Water Quality Classification Based on Minimum Qualitative Parameter (Case Study: Karun River),” JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 70, no. 3 , pp. 583–595, 2017, [Online]. Available: https://sid.ir/paper/195087/en

Related Journal Papers