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http://dx.doi.org/10.9720/kseg.2018.4.741

Site Selection Method by AHP-based Artificial Neural Network Model for Groundwater Artificial Recharge  

Kim, Gyoo-Bum (Department of Construction Safety and Disaster Prevention, Daejeon University)
Choi, Myoung-Rak (Department of Construction Safety and Disaster Prevention, Daejeon University)
Seo, Min-Ho (Industry-Academic Cooperation Foundation, Daejeon University)
Publication Information
The Journal of Engineering Geology / v.28, no.4, 2018 , pp. 741-753 More about this Journal
Abstract
Local drought in South Korea has recently increased interest in the efficient use of groundwater and then induces a growing need to introduce artificial recharge of groundwater that stores water in sedimentary layer. In order to evaluate the potential artificial recharge sites in the alluvial basins in Chungcheongnamdo province, an AHP (Analytical hierarchy process) model consisting of three primary and seven secondary factors was developed in this study. In the AHP model, adding candidate sites changes final evaluation score through a mathematical calculation process. By contrast ANN (Artificial neural network) model always provides an unchanged score for each candidate area. Therefore, the score can be used as a selection criterion for artificial recharge sites. It is concluded that the possibility of artificial recharge is relatively low if the score of the ANN model is less than about 1.5. Further studies and field surveys on the other regions in Korea will lead to draw out a more applicable ANN model.
Keywords
drought; groundwater; artificial recharge; AHP; Artificial neural network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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