3-D Modeling of groundwater table using artificial neural network- case study of Babol
IR@NISCAIR: CSIR-NISCAIR, New Delhi - ONLINE PERIODICALS REPOSITORY (NOPR)
View Archive Info| Field | Value | |
| Creator |
Choobbasti, A.J.
Shooshpasha, E. Farrokhzad, F. |
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| Date |
2013-12-13T12:48:40Z
2013-12-13T12:48:40Z 2013-11 |
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| Identifier |
0975-1033 (Online); 0379-5136 (Print)
http://hdl.handle.net/123456789/24815 |
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| Description |
903-906
In present study the artificial neural network is used as a non-linear statistical data modeling tool for assessing the 3-D model of soil's saturated depth and prediction of ground water table in study area. Based on the obtained results, it can be stated that the trained neural network is capable in 3-D modeling of groundwater table with an acceptable level of confidence and it should be added that the mentioned artificial neural network (ANN) is useful to model complex relationships between input and outputs or to find patterns in data for prediction of ground water table in study area. |
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| Language |
en_US
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| Publisher |
NISCAIR-CSIR, India
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| Rights |
<img src='http://nopr.niscair.res.in/image/cc-license-sml.png'> <a href='http://creativecommons.org/licenses/by-nc-nd/2.5/in' target='_blank'>CC Attribution-Noncommercial-No Derivative Works 2.5 India</a>
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| Source |
IJMS Vol.42(7) [November 2013]
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| Subject |
Groundwater table
Artificial neural network 3-D modeling Babol |
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| Title |
3-D Modeling of groundwater table using artificial neural network- case study of Babol
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| Type |
Article
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