Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models
In this study is predicted the groundwater level of Sharif Abad catchment using some artificial intelligence models. For this purpose used of monthly groundwater levels for modeling in the three observed wells located in the Sharif Abad watershed of Qom. To compare the results of the hybrid model of...
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| Language: | fas |
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Kharazmi University
2016-09-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2685-en.pdf |
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| description | In this study is predicted the groundwater level of Sharif Abad catchment using some artificial intelligence models. For this purpose used of monthly groundwater levels for modeling in the three observed wells located in the Sharif Abad watershed of Qom. To compare the results of the hybrid model of wavelet analysis-neural network (WNN), genetic programming (GP) multiple linear regression (MLR) and artificial neural network (ANN), two criteria of root mean squared error (RMSE) and nash-sutcliffe coefficient of efficiency (E) is used. The results of the study indicated that the WNN models provide more accurate monthly groundwater level predicted in compared to the ANN, GP and MLR models so the nash-sutcliffe coefficient in WANN model for piezometers 1, 2 and 3 are 0.98, 0.98 and 0.95, respectively.
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| format | Article |
| id | doaj-art-c70167a952f34e7abcdb80d107afcb1e |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2016-09-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-c70167a952f34e7abcdb80d107afcb1e2025-01-31T17:23:18ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382016-09-011642726Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models012 In this study is predicted the groundwater level of Sharif Abad catchment using some artificial intelligence models. For this purpose used of monthly groundwater levels for modeling in the three observed wells located in the Sharif Abad watershed of Qom. To compare the results of the hybrid model of wavelet analysis-neural network (WNN), genetic programming (GP) multiple linear regression (MLR) and artificial neural network (ANN), two criteria of root mean squared error (RMSE) and nash-sutcliffe coefficient of efficiency (E) is used. The results of the study indicated that the WNN models provide more accurate monthly groundwater level predicted in compared to the ANN, GP and MLR models so the nash-sutcliffe coefficient in WANN model for piezometers 1, 2 and 3 are 0.98, 0.98 and 0.95, respectively. .http://jgs.khu.ac.ir/article-1-2685-en.pdfsharif abad plaingroundwater levelneural networkwavelet analysisgenetic programming |
| spellingShingle | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models تحقیقات کاربردی علوم جغرافیایی sharif abad plain groundwater level neural network wavelet analysis genetic programming |
| title | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models |
| title_full | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models |
| title_fullStr | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models |
| title_full_unstemmed | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models |
| title_short | Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models |
| title_sort | prediction of groundwater level sharif abad catchment of qom using wann and gp models |
| topic | sharif abad plain groundwater level neural network wavelet analysis genetic programming |
| url | http://jgs.khu.ac.ir/article-1-2685-en.pdf |