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Estimating Ore Grade Using Evolutionary Machine Learning Models
Estimating Ore Grade Using Evolutionary Machine Learning Models
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Author(s): Ehteram, Mohammad
Khozani, Zohreh Sheikh
ISBN No.: 9789811981081
Pages: xiii, 101
Year: 202312
Format: Trade Paper
Price: $ 215.07
Dispatch delay: Dispatched between 7 to 15 days
Status: Available

Mohammad Ehtearm is a Researcher in the field of artificial intelligence. He has a Ph.D. in civil engineering. His research interests generally lie in the areas application of remote sensing in water resources, water, energy, and food nexus, extreme hydrological events, river engineering, remote sensing in water resources, dam and hydropower operation, geotechnical engineering, mining engineering, artificial intelligence, and remote sensing in mining engineering. Zohreh Sheikh Khozani is a Scientific Researcher in the field of civil engineering and mining engineering. The scope of her current research is covering hydraulic structures, hydrology, water resources engineering, environmental engineering, and the implementation of data analytics, geotechnical engineering, mining engineering, and artificial intelligence models. Saeed Soltani-Mohammadi is Associate Professor at Department of Mining Engineering, University of Kashan, Iran.


He holds a PhD on mining engineering from the Amirkabir University of technology in 2009. His research spans application of artificial intelligence and optimization methods in geosciences and mining problems. He developed many soft computing models based on practical applications for mining engineering. Maliheh Abbaszadeh is Assistant Professor at Department of Mining Engineering, University of Kashan, Iran. She holds a Ph.D. in mining engineering from the Amirkabir University of technology in 2014. She developed her teaching activity in the areas of geochemical exploration, remote sensing and machine learning algorithms.


Her primary research interest is application of machine learning algorithms in exploratory data analysis.


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