TY  - GEN
AU  - Ganguli,Rajive
AU  - Dessureault,Sean
AU  - Rogers,Pratt
AU  - Ganguli,Rajive
AU  - Dessureault,Sean
AU  - Rogers,Pratt
TI  - Advances in Computational Intelligence Applications in the Mining Industry
SN  - books978-3-0365-3158-8
PY  - 2022///
CY  - Basel
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - Technology: general issues
KW  - bicssc
KW  - History of engineering & technology
KW  - truck dispatching
KW  - mining equipment uncertainties
KW  - orebody uncertainty
KW  - discrete event simulation
KW  - Q-learning
KW  - grinding circuits
KW  - minerals processing
KW  - random forest
KW  - decision trees
KW  - machine learning
KW  - knowledge discovery
KW  - variable importance
KW  - mineral prospectivity mapping
KW  - random forest algorithm
KW  - epithermal gold
KW  - unstructured data
KW  - blast impact
KW  - empirical model
KW  - mining
KW  - fragmentation
KW  - mine worker fatigue
KW  - random forest model
KW  - health and safety management
KW  - stockpiles
KW  - operational data
KW  - mine-to-mill
KW  - geostatistics
KW  - ore control
KW  - mine optimization
KW  - digital twin
KW  - modes of operation
KW  - geological uncertainty
KW  - multivariate statistics
KW  - partial least squares regression
KW  - oil sands
KW  - bitumen extraction
KW  - bitumen processability
KW  - mine safety and health
KW  - accidents
KW  - narratives
KW  - natural language processing
KW  - random forest classification
KW  - hyperspectral imaging
KW  - multispectral imaging
KW  - dimensionality reduction
KW  - neighbourhood component analysis
KW  - artificial intelligence
KW  - mining exploitation
KW  - masonry buildings
KW  - damage risk analysis
KW  - Bayesian network
KW  - Naive Bayes
KW  - Bayesian Network Structure Learning (BNSL)
KW  - rock type
KW  - mining geology
KW  - bluetooth beacon
KW  - classification and regression tree
KW  - gaussian naïve bayes
KW  - k-nearest neighbors
KW  - support vector machine
KW  - transport route
KW  - transport time
KW  - underground mine
KW  - tactical geometallurgy
KW  - data analytics in mining
KW  - ball mill throughput
KW  - measurement while drilling
KW  - non-additivity
KW  - coal
KW  - petrographic analysis
KW  - macerals
KW  - image analysis
KW  - semantic segmentation
KW  - convolutional neural networks
KW  - point cloud scaling
KW  - fragmentation size analysis
KW  - structure from motion
KW  - n/a
N1  - Open Access
N2  - This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners
UR  - https://mdpi.com/books/pdfview/book/4987
UR  - https://directory.doabooks.org/handle/20.500.12854/79603
ER  -