3-D Modeling of groundwater table using artificial neural network-case study of Babol

被引：0
|
作者：
Choobbasti, A. J. [1 ]
Shooshpasha, E.
Farrokhzad, F.
机构：
[1] Babol Univ Technol, Dept Civil Engn, Babol Sar, Mazandaran, Iran
来源：
INDIAN JOURNAL OF GEO-MARINE SCIENCES | 2013年 / 42卷 / 07期
关键词：
Groundwater table; Artificial neural network; 3-D modeling; Babol; MAZANDARAN; PREDICTION;
D O I：
暂无
中图分类号：
P7 [海洋学];
学科分类号：
0707 ;
摘要：
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.
引用
收藏
页码：903 / 906
页数：4
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