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Author : Hoon Seo
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (114 download)
Download or read book Estimating Mineral Distribution Using Machine Learning Models written by Hoon Seo and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Mohammad Ehteram
Publisher : Springer Nature
ISBN 13 : 981198106X
Total Pages : 109 pages
Book Rating : 4.8/5 (119 download)
Download or read book Estimating Ore Grade Using Evolutionary Machine Learning Models written by Mohammad Ehteram and published by Springer Nature. This book was released on 2022-12-27 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the abilities of new machine learning models for predicting ore grade in mining engineering. A variety of case studies are examined in this book. A motivation for preparing this book was the absence of robust models for estimating ore grade. Models of current books can also be used for the different sciences because they have high capabilities for estimating different variables. Mining engineers can use the book to determine the ore grade accurately. This book helps identify mineral-rich regions for exploration and exploitation. Exploration costs can be decreased by using the models in the current book. In this book, the author discusses the new concepts in mining engineering, such as uncertainty in ore grade modeling. Ensemble models are presented in this book to estimate ore grade. In the book, readers learn how to construct advanced machine learning models for estimating ore grade. The authors of this book present advanced and hybrid models used to estimate ore grade instead of the classic methods such as kriging. The current book can be used as a comprehensive handbook for estimating ore grades. Industrial managers and modelers can use the models of the current books. Each level of ore grade modeling is explained in the book. In this book, advanced optimizers are presented to train machine learning models. Therefore, the book can also be used by modelers in other fields. The main motivation of this book is to address previous shortcomings in the modeling process of ore grades. The scope of this book includes mining engineering, soft computing models, and artificial intelligence.
Author : Sridhar Dutta
Publisher :
ISBN 13 :
Total Pages : 378 pages
Book Rating : 4.:/5 (725 download)
Download or read book Predictive Performance of Machine Learning Algorithms for Ore Reserve Estimation in Sparse and Imprecise Data written by Sridhar Dutta and published by . This book was released on 2006 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditional geostatistical estimation techniques have been used predominantly in the mining industry for the purpose of ore reserve estimation. Determination of mineral reserve has always posed considerable challenge to mining engineers due to geological complexities that are generally associated with the phenomenon of ore body formation. Considerable research over the years has resulted in the development of a number of state-of-the-art methods for the task of predictive spatial mapping such as ore reserve estimation. Recent advances in the use of the machine learning algorithms (MLA) have provided a new approach to solve the age-old problem. Therefore, this thesis is focused on the use of two MLA, viz. the neural network (NN) and support vector machine (SVM), for the purpose of ore reserve estimation. Application of the MLA have been elaborated with two complex drill hole datasets. The first dataset is a placer gold drill hole data characterized by high degree of spatial variability, sparseness and noise while the second dataset is obtained from a continuous lode deposit. The application and success of the models developed using these MLA for the purpose of ore reserve estimation depends to a large extent on the data subsets on which they are trained and subsequently on the selection of the appropriate model parameters. The model data subsets obtained by random data division are not desirable in sparse data conditions as it usually results in statistically dissimilar subsets, thereby reducing their applicability. Therefore, an ideal technique for data subdivision has been suggested in the thesis. Additionally, issues pertaining to the optimum model development have also been discussed. To investigate the accuracy and the applicability of the MLA for ore reserve estimation, their generalization ability was compared with the geostatistical ordinary kriging (OK) method. The analysis of Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Error (ME) and the coefficient of determination (R2) as the indices of the model performance indicated that they may significantly improve the predictive ability and thereby reduce the inherent risk in ore reserve estimation"--Leaf iii.
Author : E.J.M. Carranza
Publisher : Elsevier
ISBN 13 : 008093031X
Total Pages : 365 pages
Book Rating : 4.0/5 (89 download)
Download or read book Geochemical Anomaly and Mineral Prospectivity Mapping in GIS written by E.J.M. Carranza and published by Elsevier. This book was released on 2008-11-26 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geochemical Anomaly and Mineral Prospectivity Mapping in GIS documents and explains, in three parts, geochemical anomaly and mineral prospectivity mapping by using a geographic information system (GIS). Part I reviews and couples the concepts of (a) mapping geochemical anomalies and mineral prospectivity and (b) spatial data models, management and operations in a GIS. Part II demonstrates GIS-aided and GIS-based techniques for analysis of robust thresholds in mapping of geochemical anomalies. Part III explains GIS-aided and GIS-based techniques for spatial data analysis and geo-information sybthesis for conceptual and predictive modeling of mineral prospectivity. Because methods of geochemical anomaly mapping and mineral potential mapping are highly specialized yet diverse, the book explains only methods in which GIS plays an important role. The book avoids using language and functional organization of particular commercial GIS software, but explains, where necessary, GIS functionality and spatial data structures appropriate to problems in geochemical anomaly mapping and mineral potential mapping. Because GIS-based methods of spatial data analysis and spatial data integration are quantitative, which can be complicated to non-numerate readers, the book simplifies explanations of mathematical concepts and their applications so that the methods demonstrated would be useful to professional geoscientists, to mineral explorationists and to research students in fields that involve analysis and integration of maps or spatial datasets. The book provides adequate illustrations for more thorough explanation of the various concepts. Explains GIS functionality and spatial data structures appropriate regardless of the particular GIS software in use Simplifies explanation of mathematical concepts and application Illustrated for more thorough explanation of concepts
Author : Mario E. Rossi
Publisher : Springer Science & Business Media
ISBN 13 : 1402057172
Total Pages : 337 pages
Book Rating : 4.4/5 (2 download)
Download or read book Mineral Resource Estimation written by Mario E. Rossi and published by Springer Science & Business Media. This book was released on 2013-12-21 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mineral resource estimation has changed considerably in the past 25 years: geostatistical techniques have become commonplace and continue to evolve; computational horsepower has revolutionized all facets of numerical modeling; mining and processing operations are often larger; and uncertainty quantification is becoming standard practice. Recent books focus on historical methods or details of geostatistical theory. So there is a growing need to collect and synthesize the practice of modern mineral resource estimation into a book for undergraduate students, beginning graduate students, and young geologists and engineers. It is especially fruitful that this book is written by authors with years of relevant experience performing mineral resource estimation and with years of relevant teaching experience. This comprehensive textbook and reference fills this need.
Author : Ron Jenkins
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 440 pages
Book Rating : 4.4/5 (91 download)
Download or read book Introduction to X-Ray Powder Diffractometry written by Ron Jenkins and published by Wiley-Interscience. This book was released on 1996-07-12 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: When bombarded with X-rays, solid materials produce distinct scattering patterns similar to fingerprints. X-ray powder diffraction is a technique used to fingerprint solid samples, which are then identified and cataloged for future use-much the way the FBI keeps fingerprints on file. The current database of some 70,000 material prints has been put to a broad range of uses, from the analysis of moon rocks to testing drugs for purity. Introduction to X-ray Powder Diffractometry fully updates the achievements in the field over the past fifteen years and provides a much-needed explanation of the state-of-the-art techniques involved in characterizing materials. It covers the latest instruments and methods, with an emphasis on the fundamentals of the diffractometer, its components, alignment, calibration, and automation. The first three chapters outline diffraction theory in clear language, accessible to both students and professionals in chemistry, physics, geology, and materials science. The book's middle chapters describe the instrumentation and procedures used in X-ray diffraction, including X-ray sources, X-ray detection, and production of monochromatic radiation. The chapter devoted to instrument design and calibration is followed by an examination of specimen preparation methods, data collection, and reduction. The final two chapters provide in-depth discussions of qualitative and quantitative analysis. While the material is presented in an orderly progression, beginning with basic concepts and moving on to more complex material, each chapter stands on its own and can be studied independently or used as a professional reference. More than 230 illustrations and tables demonstrate techniques and clarify complex material. Self-contained, timely, and user-friendly, Introduction to X-ray Powder Diffractometry is an enormously useful text and professional reference for analytical chemists, physicists, geologists and materials scientists, and upper-level undergraduate and graduate students in materials science and analytical chemistry. X-ray powder diffraction-a technique that has matured significantly in recent years-is used to identify solid samples and determine their composition by analyzing the so-called "fingerprints" they generate when X-rayed. This unique volume fulfills two major roles: it is the first textbook devoted solely to X-ray powder diffractometry, and the first up-to-date treatment of the subject in 20 years. This timely, authoritative volume features: * Clear, concise descriptions of both theory and practice-including fundamentals of diffraction theory and all aspects of the diffractometer * A treatment that reflects current trends toward automation, covering the newest instrumentation and automation techniques * Coverage of all the most common applications, with special emphasis on qualitative and quantitative analysis * An accessible presentation appropriate for both students and professionals * More than 230 tables and illustrations Introduction to X-ray Powder Diffractometry, a collaboration between two internationally known and respected experts in the field, provides invaluable guidance to anyone using X-ray powder diffractometers and diffractometry in materials science, ceramics, the pharmaceutical industry, and elsewhere.
Author : B. L. Chatterji
Publisher :
ISBN 13 : 9781681171470
Total Pages : 0 pages
Book Rating : 4.1/5 (714 download)
Download or read book Mineral Resource Estimation written by B. L. Chatterji and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of estimating a Mineral Resource can only take place after the estimator is convinced of the soundness of the fundamentals underlying the estimation process. Thus the database of sampling, density, and other quality data for both estimation and geological interpretation must have integrity and robustness ; the geological data must be sufficiently complete for the definition of a geological model; the geological model itself must have internal consistency, should explain the observed arrangement of lithological and mineralogical domains, and should represent the estimator's best knowledge of the genesis of the mineral deposit; and the geological model should support the distribution of mineralisation seen in the sampling. It is only at this stage that a resource model may be generated.
Author : Christoph Mueller
Publisher : CRC Press
ISBN 13 : 1000439062
Total Pages : 782 pages
Book Rating : 4.0/5 (4 download)
Download or read book Mining goes Digital written by Christoph Mueller and published by CRC Press. This book was released on 2019-05-22 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: The conferences on ‘Applications for Computers and Operations Research in the Minerals Industry’ (APCOM) initially focused on the optimization of geostatistics and resource estimation. Several standard methods used in these fields were presented in the early days of APCOM. While geostatistics remains an important part, information technology has emerged, and nowadays APCOM not only focuses on geostatistics and resource estimation, but has broadened its horizon to Information and Communication Technology (ICT) in the mineral industry. Mining Goes Digital is a collection of 90 high quality, peer reviewed papers covering recent ICT-related developments in: - Geostatistics and Resource Estimation - Mine Planning - Scheduling and Dispatch - Mine Safety and Mine Operation - Internet of Things, Robotics - Emerging Technologies - Synergies from other industries - General aspects of Digital Transformation in Mining Mining Goes Digital will be of interest to professionals and academics involved or interested in the above-mentioned areas.
Author : Alastair J. Sinclair
Publisher : Cambridge University Press
ISBN 13 : 1139433598
Total Pages : 403 pages
Book Rating : 4.1/5 (394 download)
Download or read book Applied Mineral Inventory Estimation written by Alastair J. Sinclair and published by Cambridge University Press. This book was released on 2006-01-19 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents an applied approach to the estimation of mineral resources/reserves. It is suitable for any university or mining school that offers courses on mineral resource/reserve estimation. It will also be valuable for professional mining and geological engineers and geologists working with mineral exploration companies.
Author : M. David
Publisher : Elsevier
ISBN 13 : 0444597611
Total Pages : 385 pages
Book Rating : 4.4/5 (445 download)
Download or read book Geostatistical Ore Reserve Estimation written by M. David and published by Elsevier. This book was released on 2012-12-02 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in Geomathematics, 2: Geostatistical Ore Reserve Estimation focuses on the methodologies, processes, and principles involved in geostatistical ore reserve estimation, including the use of variogram, sampling, theoretical models, and variances and covariances. The publication first takes a look at elementary statistical theory and applications; contribution of distributions to mineral reserves problems; and evaluation of methods used in ore reserve calculations. Concerns cover estimation problems during a mine life, origin and credentials of geostatistics, precision of a sampling campaign and prediction of the effect of further sampling, exercises on grade-tonnage curves, theoretical models of distributions, and computational remarks on variances and covariances. The text then examines variogram and the practice of variogram modeling. Discussions focus on solving problems in one dimension, linear combinations and average values, theoretical models of isotropic variograms, the variogram as a geological features descriptor, and the variogram as the fundamental function in error computations. The manuscript ponders on statistical problems in sample preparation, orebody modeling, grade-tonnage curves, ore-waste selection, and planning problems, the practice of kriging, and the effective computation of block variances. The text is a valuable source of data for researchers interested in geostatistical ore reserve estimation.
Author : Donald Singer
Publisher : Oxford University Press
ISBN 13 : 0199742103
Total Pages : 232 pages
Book Rating : 4.1/5 (997 download)
Download or read book Quantitative Mineral Resource Assessments written by Donald Singer and published by Oxford University Press. This book was released on 2010-03-23 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Policy makers, mineral exploration experts, and regional planners decide how public lands, which may contain undiscovered resources, should be used or whether to invest in exploration for minerals on a regular basis. Decisions are also made concerning mineral resource adequacy, national policy, and regional development. This book makes explicit the factors that can affect a mineral-related decision so that decision-makers can clearly see the possible consequences of their decisions. Based on work done at the US Geological Survey, the authors address the question of the kinds of issues decision-makers are trying to resolve and what forms of information would aid in resolving these issues. The goal of the process discussed is to offer unbiased quantitative assessments in a format needed in decision-support systems so that consequences of alternative courses of action can be examined with respect to land use or mineral-resource development. An integrated approach focuses on three assessment parts and the models that support them. Although the concepts presented are straightforward and understandable, in assessments, carefully listening to the experts in other disciplines leads to better products. Navigating through and making sense of QRA requires not just learning rules and equations, but life experiences and common sense. The judgment required to understand which tools to apply are best learned by example and experience. This will be useful to governmental or industrial policy makers, managers of explorations, planners of regional development, and similar decision-makers.
Author : Daniel Asante Otchere
Publisher : CRC Press
ISBN 13 : 1003860192
Total Pages : 322 pages
Book Rating : 4.0/5 (38 download)
Download or read book Data Science and Machine Learning Applications in Subsurface Engineering written by Daniel Asante Otchere and published by CRC Press. This book was released on 2024-02-06 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary focus of the field of machine learning (ML). ML aims to develop data-driven methods and computational algorithms that can learn to identify complex and non-linear patterns to understand and predict the relationships between variables by analysing extensive data. Although ML models provide the final output for predictions, several steps need to be performed to achieve accurate predictions. These steps, data pre-processing, feature selection, feature engineering and outlier removal, are all contained in this book. New models are also developed using existing ML architecture and learning theories to improve the performance of traditional ML models and handle small and big data without manual adjustments. This research-oriented book will help subsurface engineers, geophysicists, and geoscientists become familiar with data science and ML advances relevant to subsurface engineering. Additionally, it demonstrates the use of data-driven approaches for salt identification, seismic interpretation, estimating enhanced oil recovery factor, predicting pore fluid types, petrophysical property prediction, estimating pressure drop in pipelines, bubble point pressure prediction, enhancing drilling mud loss, smart well completion and synthetic well log predictions.
Author : Antonios K. Alexandridis
Publisher : John Wiley & Sons
ISBN 13 : 1118596293
Total Pages : 262 pages
Book Rating : 4.1/5 (185 download)
Download or read book Wavelet Neural Networks written by Antonios K. Alexandridis and published by John Wiley & Sons. This book was released on 2014-04-24 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.
Author : Oliver Kramer
Publisher : Springer Science & Business Media
ISBN 13 : 3642386520
Total Pages : 137 pages
Book Rating : 4.6/5 (423 download)
Download or read book Dimensionality Reduction with Unsupervised Nearest Neighbors written by Oliver Kramer and published by Springer Science & Business Media. This book was released on 2013-05-30 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results.
Author : Jonathan P. Zehr
Publisher : Springer Nature
ISBN 13 : 303067746X
Total Pages : 191 pages
Book Rating : 4.0/5 (36 download)
Download or read book Marine Nitrogen Fixation written by Jonathan P. Zehr and published by Springer Nature. This book was released on 2021-04-02 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to serve as a centralized reference document for students and researchers interested in aspects of marine nitrogen fixation. Although nitrogen is a critical element in both terrestrial and aquatic productivity, and nitrogen fixation is a key process that balances losses due to denitrification in both environments, most resources on the subject focuses on the biochemistry and microbiology of such processes and the organisms involved in the terrestrial environment on symbiosis in terrestrial systems, or on largely ecological aspects in the marine environment. This book is intended to provide an overview of N2 fixation research for marine researchers, while providing a reference on marine research for researchers in other fields, including terrestrial N2 fixation. This book bridges this knowledge gap for both specialists and non-experts, and provides an in-depth overview of the important aspects of nitrogen fixation as it relates to the marine environment. This resource will be useful for researchers in the specialized field, but also useful for scientists in other disciplines who are interested in the topic. It would provide a possible text for upper division classes or graduate seminars.
Author : G. Gaal
Publisher : Elsevier
ISBN 13 : 1483287084
Total Pages : 480 pages
Book Rating : 4.4/5 (832 download)
Download or read book Computer Applications in Resource Estimation written by G. Gaal and published by Elsevier. This book was released on 2013-10-22 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative resource assessment methods play an increasing role in exploration for petroleum, water and minerals. This volume presents an international review on the state-of-the-art of the computerized methodology in resource exploration. The papers taken from those presented at the symposium are classified to either techniques, i.e., trend analysis; classification techniques; geostatistics; image analysis; expert systems/artificial intelligence; inventories; tomography and others, or to resources, i.e., petroleum, water, metals and non-metals.
Author : Issam El Naqa
Publisher : Springer
ISBN 13 : 3319183052
Total Pages : 336 pages
Book Rating : 4.3/5 (191 download)
Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
