Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region

Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region

Quantification of the soil physicochemical properties is one of the essential process in the field of soil geo-science. In the current research, three types of machine learning (ML) models including support vector machine (SVM), random forest (RF), and gradient boosted decision tree (GBDT) were deve...

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Bibliographic Details
Main Authors: Neeraj Dhanraj Bokde, Zainab Hasan Ali, Maysam Th. Al-Hadidi, Aitazaz Ahsan Farooque, Mehdi Jamei, Ali Abdulridha Al Maliki, Beste Hamiye Beyaztas, Hossam Faris, Zaher Mundher Yaseen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Soil physicochemical properties
total dissolved salt
machine learning
correlation analysis
Online Access:https://ieeexplore.ieee.org/document/9395118/

Internet

https://ieeexplore.ieee.org/document/9395118/

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