Estimating the permeability coefficient of soil using CART and GMDH approaches
Permeability coefficient of soil (k) is one of the most important parameters in groundwater studies. This study, two robust explicit data-driven methods, Including classification and regression trees (CART) and the group method of data handling (GMDH) were developed using the characteristics of soil...
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-08-01
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| Series: | Water Supply |
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| Online Access: | http://ws.iwaponline.com/content/22/8/6756 |
| _version_ | 1811262159972204544 |
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| author | Mina Torabi Hamed Sarkardeh S. Mohammad Mirhosseini |
| author_facet | Mina Torabi Hamed Sarkardeh S. Mohammad Mirhosseini |
| author_sort | Mina Torabi |
| collection | DOAJ |
| description | Permeability coefficient of soil (k) is one of the most important parameters in groundwater studies. This study, two robust explicit data-driven methods, Including classification and regression trees (CART) and the group method of data handling (GMDH) were developed using the characteristics of soil, i.e., clay content (CC), water content (ω), liquid limit (LL), plastic limit (PL), specific density (γ), void ratio (e) to generate predictive equations for prediction of k. When compared to CART; mean absolute error (MAE) = 0.0051, root mean square error (RMSE) = 0.0088, scatter index (SI) = 64.00%, correlation coefficient (R) = 0.7841, index of agreement (IA) = 0.8830; the GMDH equation produced the lowest error values; MAE = 0.0044, RMSE = 0.0072, SI = 52.17%, R = 0.8493, Ia = 0.9184; in testing stage. Although, GMDH had better performance, however, CART and GMDH could be considered effective approaches for the prediction of k.
HIGHLIGHTS
Two predictive models were developed to estimate the permeability coefficient of soil.;
GMDH and CART algorithms were evaluated in this study.;
GMDH provided more accurate results when compared to CART for the prediction of permeability coefficient of soil.;
The water content was the most effective parameter for determining the permeability coefficient of soil.;
Field data were used in this research.; |
| first_indexed | 2024-04-12T19:20:15Z |
| format | Article |
| id | doaj.art-34ed7df414da4192852fb98f166ec164 |
| institution | Directory Open Access Journal |
| issn | 1606-9749 1607-0798 |
| language | English |
| last_indexed | 2024-04-12T19:20:15Z |
| publishDate | 2022-08-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Supply |
| spelling | doaj.art-34ed7df414da4192852fb98f166ec1642022-12-22T03:19:37ZengIWA PublishingWater Supply1606-97491607-07982022-08-012286756676410.2166/ws.2022.248248Estimating the permeability coefficient of soil using CART and GMDH approachesMina Torabi0Hamed Sarkardeh1S. Mohammad Mirhosseini2 Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran Department of Civil Engineering, Faculty of Engineering, Hakim Sabzevari University, Sabzevar, Iran Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran Permeability coefficient of soil (k) is one of the most important parameters in groundwater studies. This study, two robust explicit data-driven methods, Including classification and regression trees (CART) and the group method of data handling (GMDH) were developed using the characteristics of soil, i.e., clay content (CC), water content (ω), liquid limit (LL), plastic limit (PL), specific density (γ), void ratio (e) to generate predictive equations for prediction of k. When compared to CART; mean absolute error (MAE) = 0.0051, root mean square error (RMSE) = 0.0088, scatter index (SI) = 64.00%, correlation coefficient (R) = 0.7841, index of agreement (IA) = 0.8830; the GMDH equation produced the lowest error values; MAE = 0.0044, RMSE = 0.0072, SI = 52.17%, R = 0.8493, Ia = 0.9184; in testing stage. Although, GMDH had better performance, however, CART and GMDH could be considered effective approaches for the prediction of k. HIGHLIGHTS Two predictive models were developed to estimate the permeability coefficient of soil.; GMDH and CART algorithms were evaluated in this study.; GMDH provided more accurate results when compared to CART for the prediction of permeability coefficient of soil.; The water content was the most effective parameter for determining the permeability coefficient of soil.; Field data were used in this research.;http://ws.iwaponline.com/content/22/8/6756decision treesexplicit modelsinfiltrationksoft computing |
| spellingShingle | Mina Torabi Hamed Sarkardeh S. Mohammad Mirhosseini Estimating the permeability coefficient of soil using CART and GMDH approaches Water Supply decision trees explicit models infiltration k soft computing |
| title | Estimating the permeability coefficient of soil using CART and GMDH approaches |
| title_full | Estimating the permeability coefficient of soil using CART and GMDH approaches |
| title_fullStr | Estimating the permeability coefficient of soil using CART and GMDH approaches |
| title_full_unstemmed | Estimating the permeability coefficient of soil using CART and GMDH approaches |
| title_short | Estimating the permeability coefficient of soil using CART and GMDH approaches |
| title_sort | estimating the permeability coefficient of soil using cart and gmdh approaches |
| topic | decision trees explicit models infiltration k soft computing |
| url | http://ws.iwaponline.com/content/22/8/6756 |
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