FORECASTING SOME OF THE QUALITATIVE PARAMETERS OF RIVERS USING WAVELET ARTIFICIAL NEURAL NETWORK HYBRID (W-ANN) MODEL (CASE OF STUDY: JAJROUD RIVER OF TEHRAN AND GHARASO RIVER OF KERMANSHAH)

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.

BANEJAD HOSSEIN; KAMALI MAHSA; AMIRMORADI KIMIA; OLYAIE EHSAN

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

Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT Year:2013 | Volume:6 | Issue:3 Page(s): 277-294

Download Full-Text

Persian Verion

View:

932

Download:

Cites:

Information Journal Paper

Title

FORECASTING SOME OF THE QUALITATIVE PARAMETERS OF RIVERS USING WAVELET ARTIFICIAL NEURAL NETWORK HYBRID (W-ANN) MODEL (CASE OF STUDY: JAJROUD RIVER OF TEHRAN AND GHARASO RIVER OF KERMANSHAH)

Author(s)

BANEJAD HOSSEIN | KAMALI MAHSA | AMIRMORADI KIMIA | OLYAIE EHSAN | Issue Writer Certificate

Keywords

JAJROUD RIVER OF TEHRANQ2

GHARASO RIVER OF KERMANSHAH TOTAL DISSOLVED SOLIDSQ2

WAVELET ARTIFICIAL NEURAL NETWORKQ2

SODIUM ABSORPTION RATEQ2

ELECTRICAL CONDUCTIVITYQ2

Abstract

Background and Objectives: Rivers are the most important resources supplying drinking, agricultural, and industrial water demand. Their quality fluctuates frequently due to crossing from different regions and beds as well as their direct relationship with their peripheral environments.Thus, it is essential to be considered the surveying and predicating changes in the water qualitative parameters in a river. In this study, in order to estimate some of the qualitative parameters (Total dissolved solids, ELECTRICAL CONDUCTIVITY and SODIUM ABSORPTION RATE) for Tehran Jajroud and Kermanshah Gharasu rivers, we used wavelet-artificial neural network (W-ANN) hybrid model during a statistical period of 24 years.Material and Methods: We compared W-ANN model with ANN model in order to evaluate its capability in detecting signals and separating error signals for estimating water quality parameters of the abovementioned rivers. The evaluation of both models was performed by the statistical criteria including correlation coefficient, the Nash-Sutcliffe model efficiency coefficient (NS), the root mean square error (RMSE) and the mean absolute error (MAE).Results: The results showed that the optimized W-ANN with correlation coefficient of 0.9 has high capability to estimate SAR parameter in the stations studied. Moreover, we found that W-ANN had less error and higher accuracy in the case of EC and TDS parameters rather than ANN model.Conclusion: W-ANN proved high efficiency in forecasting of the water quality parameters of rivers, therefore, it can be used for decision making and assurance of monitoring results and optimizing the monitoring costs.

Cites

No record.

References

No record.

Cite

APA: Copy

BANEJAD, HOSSEIN, KAMALI, MAHSA, AMIRMORADI, KIMIA, & OLYAIE, EHSAN. (2013). FORECASTING SOME OF THE QUALITATIVE PARAMETERS OF RIVERS USING WAVELET ARTIFICIAL NEURAL NETWORK HYBRID (W-ANN) MODEL (CASE OF STUDY: JAJROUD RIVER OF TEHRAN AND GHARASO RIVER OF KERMANSHAH). IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, 6(3), 277-294. SID. https://sid.ir/paper/145764/en

Vancouver: Copy

BANEJAD HOSSEIN, KAMALI MAHSA, AMIRMORADI KIMIA, OLYAIE EHSAN. FORECASTING SOME OF THE QUALITATIVE PARAMETERS OF RIVERS USING WAVELET ARTIFICIAL NEURAL NETWORK HYBRID (W-ANN) MODEL (CASE OF STUDY: JAJROUD RIVER OF TEHRAN AND GHARASO RIVER OF KERMANSHAH). IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT[Internet]. 2013;6(3):277-294. Available from: https://sid.ir/paper/145764/en

IEEE: Copy

HOSSEIN BANEJAD, MAHSA KAMALI, KIMIA AMIRMORADI, and EHSAN OLYAIE, “FORECASTING SOME OF THE QUALITATIVE PARAMETERS OF RIVERS USING WAVELET ARTIFICIAL NEURAL NETWORK HYBRID (W-ANN) MODEL (CASE OF STUDY: JAJROUD RIVER OF TEHRAN AND GHARASO RIVER OF KERMANSHAH),” IRANIAN JOURNAL OF HEALTH AND ENVIRONMENT, vol. 6, no. 3, pp. 277–294, 2013, [Online]. Available: https://sid.ir/paper/145764/en

Related Journal Papers