Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Entire DC Network
Modeling Of Groundwater Potential Using Cloud Computing Platform: A Case Study From Nineveh Plain, Northern Iraq, Ali Za. Al-Ozeer, Alaa M. Al-Abadi, Tariq Abed Hussain, Alan E. Fryar, Biswajeet Pradhan, Abdullah Alamri, Khairul Nizam Abdul Maulud
Modeling Of Groundwater Potential Using Cloud Computing Platform: A Case Study From Nineveh Plain, Northern Iraq, Ali Za. Al-Ozeer, Alaa M. Al-Abadi, Tariq Abed Hussain, Alan E. Fryar, Biswajeet Pradhan, Abdullah Alamri, Khairul Nizam Abdul Maulud
Earth and Environmental Sciences Faculty Publications
Knowledge of the groundwater potential, especially in an arid region, can play a major role in planning the sustainable management of groundwater resources. In this study, nine machine learning (ML) algorithms—namely, Artificial Neural Network (ANN), Decision Jungle (DJ), Averaged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), Locally-Deep Support Vector Machine (LD-SVM), Boosted Decision Tree (BDT), Logistic Regression (LG), and Support Vector Machine (SVM)—were run on the Microsoft Azure cloud computing platform to model the groundwater potential. We investigated the relationship between 512 operating boreholes with a specified specific capacity and 14 groundwater-influencing occurrence factors. The unconfined aquifer in …