Partially linear support vector machines applied to the prediction of mine slope movements

DOI10.1016/j.mcm.2009.08.036zbMath1190.68047OpenAlexW1994424427WikidataQ57838186 ScholiaQ57838186MaRDI QIDQ984150

J. Martínez

Publication date: 16 July 2010

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

Full work available at URL: https://doi.org/10.1016/j.mcm.2009.08.036

zbMATH Keywords

predictionautoregressive modelspartially linear modelsSVMmining safety

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics in engineering and industry; control charts (62P30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Learning SVM with weighted maximum margin criterion for classification of imbalanced data

Cites Work

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• Comparison of kriging and neural networks with application to the exploitation of a slate mine
• Support vector machines and gradient boosting for graphical estimation of a slate deposit
• Root-N-Consistent Semiparametric Regression
• Theory of Reproducing Kernels

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