Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS
By Yousef Razandi, Hamid Reza Pourghasemi, Najmeh Samani Neisani, Omid Rahmati. Earth Science Informatics, 2015
463 citations recorded by the source corpus.
Subfields: Environmental Engineering, Geochemistry and Petrology, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/2d533a999b9c3926008635d60a8463fe4aa482dd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Environmental Engineering
- Hamid Reza Pourghasemi
- Seyed Amir Naghibi
- Barnali Dixon
- Ozgur Kisi
- Jan Adamowski
- Kwok-Wing Chau
- Ravinesh C. Deo
- Masoud Karbasi
In Global and Planetary Change
- Hamid Reza Pourghasemi
- Seyed Amir Naghibi
- Barnali Dixon
- Ozgur Kisi
- Binh Thai Pham
- Masoud Karbasi
- Khabat Khosravi
- Indra Prakash
Citations in the corpus
- Groundwater-Potential Mapping Using a Self-Learning Bayesian Network Model: A Comparison among Metaheuristic Algorithms (2021, methodology): “3 by using the kriging interpolation method (Figure 3j) [17].”
- GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran (2015, methodology): “Traditional methods such as bivariate and multivariate models namely frequency ratio, weights-of-evidence, logistic regression, index of entropy, evidential belief function, and analytical hierarchy process which have been used in groundwater potential mapping (Oh et al. 2011; Ozdemir 2011a, b; Mana”