Annual Report 2019

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.

Please contact 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

Ortiz JM (2019) Geometallurgical modeling framework, paper 2019-01
Cevik SI, Olivo G, Ortiz JM (2019) Knowledge discovery from geochemical data with supervised and unsupervised methods, paper 2019-02
Avalos S, Ortiz JM (2019) Exploring the RCNN technique in a multiple-point statistics framework, paper 2019-03
Riquelme A, Ortiz JM (2019) Updating geological codes through iterative jack-knife, paper 2019-04
Riquelme A, Ortiz JM (2019) Modeling the uncertainty in geological volumes: the log-normal case, paper 2019-05
Riquelme A, Ortiz JM (2019) A general approach to the assessment of uncertainty in volumes by using the multi-Gaussian model, paper 2019-06
Bolgkoranou M, Ortiz JM (2019) Multivariate geostatistical simulation using Principal Component Analysis, paper 2019-07
Midkiff W, Ortiz JM (2019) A literature review of p-wave velocities in rock under compression, paper 2019-08
Ortiz JM (2019) MultiGaussian kriging: a review, paper 2019-09
Avalos SA, Kracht W, Ortiz JM (2019) Using LSTM and GRU to predict SAG mill energy consumption, paper 2019-10
Avalos S, Ortiz JM (2019) A simple, synthetic and two dimensional geometallurgical modeling application, paper 2019-11
Avalos S, Ortiz JM (2019) Convolutional neural networks architecture: a tutorial, paper 2019-12
Cevik SI, Ortiz JM (2019) Machine Learning in mineral exploration: a tutorial, paper 2019-13