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پتانسیل یابی آب زیرزمینی کارستی با استفاده از مدل یادگیری ماشین
Authors :
حسین محمد زاده
1
جعفر هاشمی
2
حمید قالیباف محمد آبادی
3
1- دانشکده علوم دانشگاه فردوسی مشهد
2- دانشکده علوم دانشگاه فردوسی مشهد
3- دانشکده علوم دانشگاه فردوسی مشهد
Keywords :
Machine learning،Karst،groundwater Potential،Random Forest،Hezar Masjed
Abstract :
The objective of this paper is to present a groundwater potential zoning map for the Hezar Masjid highlands, located northeast of Mashhad, using the Random Forest (RF) machine learning model. The zoning map was developed based on the locations of 1,438 springs in the area and 16 factors influencing groundwater potential. The model's performance was assessed using various statistical criteria, including the area under the receiver operating characteristic (ROC) curve (AUC = 0.93), indicating excellent accuracy
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