Integrated Ensemble Weight of Evidence and Logistic Regression for Potential Groundwater Mapping: An Application to the Northern Piedmont of High Atlas Mountains (Morocco)

Author:

Rahali Hassane,Elaryf Siham,Amar Hicham,Zellou Bouchra

Publisher

Springer International Publishing

Reference11 articles.

1. Ozdemir, A.: Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey). J. Hydrol. (2011). https://doi.org/10.1016/j.jhydrol.2011.05.015

2. Lee, S., Hong, S.M., Jung, H.S.: GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea. Geocarto. Int., 1–33 (2017)

3. Naghibi, S.A., Moghaddam, D.D., Kalantar, B., Pradhan, B., Kisi, O.: A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping. J. Hydrol. 548, 471–483 (2017)

4. Bonham-Carter, G.E., Cox, S.: Geographic information systems for geoscientists: modelling with GIS. In: Computer Methods in the Geosciences Pergamon, pp. 1–2. Elsevier (2010)

5. Agterberg, F.P., Bonham-Carter, G.F., Cheng, Q., Wright, D.F.: Weights of evidence modeling and weighted logistic regression for mineral potential mapping. In: Davis, J.C., Herzfeld, U.C. (eds.) Computers in Geology, pp. 13–32. Oxford University Press, New York (1993)

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