Use of machine learning techniques to analyse the risk associated with mine sludge deposits

DOI10.1016/j.mcm.2010.11.066zbMath1235.68127OpenAlexW2003234522MaRDI QIDQ409805

J. Taboada, E. Giraldez, T. Rivas, María Araújo-Fernández

Publication date: 15 April 2012

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2010.11.066

zbMATH Keywords

riskmachine learningsludge deposits

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
• Support-vector networks
• Support vector machines and gradient boosting for graphical estimation of a slate deposit
• Machine learning techniques applied to the construction of a new geomechanical quality index
• A logical calculus of the ideas immanent in nervous activity
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Use of machine learning techniques to analyse the risk associated with mine sludge deposits