The research developed during the last year is summarized in the Annual Report 2019. This report is made available to the general public for reference. Collaboration from other research groups and from industry is encouraged.
Prof. Julian M. Ortiz if you would like to discuss a collaborative project.
The contents of the Annual Report 2019 can be downloaded in a
single pdf document or as individual papers.
Table of contents
Introduction Ortiz JM (2019) , paper 2019-01 Geometallurgical modeling framework Cevik SI, Olivo G, Ortiz JM (2019) , paper 2019-02 Knowledge discovery from geochemical data with supervised and unsupervised methods Avalos S, Ortiz JM (2019) , paper 2019-03 Exploring the RCNN technique in a multiple-point statistics framework Riquelme A, Ortiz JM (2019) , paper 2019-04 Updating geological codes through iterative jack-knife Riquelme A, Ortiz JM (2019) , paper 2019-05 Modeling the uncertainty in geological volumes: the log-normal case Riquelme A, Ortiz JM (2019) , paper 2019-06 A general approach to the assessment of uncertainty in volumes by using the multi-Gaussian model Bolgkoranou M, Ortiz JM (2019) , paper 2019-07 Multivariate geostatistical simulation using Principal Component Analysis Midkiff W, Ortiz JM (2019) , paper 2019-08 A literature review of p-wave velocities in rock under compression Ortiz JM (2019) , paper 2019-09 MultiGaussian kriging: a review Avalos SA, Kracht W, Ortiz JM (2019) , paper 2019-10 Using LSTM and GRU to predict SAG mill energy consumption Avalos S, Ortiz JM (2019) , paper 2019-11 A simple, synthetic and two dimensional geometallurgical modeling application Avalos S, Ortiz JM (2019) , paper 2019-12 Convolutional neural networks architecture: a tutorial Cevik SI, Ortiz JM (2019) , paper 2019-13 Machine Learning in mineral exploration: a tutorial