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Estimating Ore Grade Using Evolutionary Machine Learning Models

This book examines the abilities of new machine learning models for predicting ore grade in mining engineering. A variety of case studies are examined in this book. A motivation for preparing this book was the absence of robust models for estimating ore grade. Models of current books can also be use...

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I tiakina i:
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Ngā kaituhi matua: Ehteram, Mohammad (Author), Khozani, Zohreh Sheikh (Author), Soltani-Mohammadi, Saeed (Author), Abbaszadeh, Maliheh (Author)
Kaituhi rangatōpū: SpringerLink (Online service)
Hōputu: Tāhiko īPukapuka
Reo:Ingarihi
I whakaputaina: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Putanga:1st ed. 2023.
Ngā marau:
Mineralogy.
Machine learning.
Artificial intelligence > Data processing.
Artificial intelligence.
Machine Learning.
Data Science.
Artificial Intelligence.
Urunga tuihono:https://doi.org/10.1007/978-981-19-8106-7
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https://doi.org/10.1007/978-981-19-8106-7

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