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Application Of Artificial Neural Network Systems To Ore Grade Estimation From Exploration Data
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Book Synopsis Application of Artificial Neural Network Systems to Ore Grade Estimation from Exploration Data by : Ioannis K. Kapageridis
Download or read book Application of Artificial Neural Network Systems to Ore Grade Estimation from Exploration Data written by Ioannis K. Kapageridis and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Application of Artificial Neural Network Systems to Grade Estimation from Exploration Data by : Ioannis Konstantinou Kapageridis
Download or read book Application of Artificial Neural Network Systems to Grade Estimation from Exploration Data written by Ioannis Konstantinou Kapageridis and published by . This book was released on 1999 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating Ore Grade Using Evolutionary Machine Learning Models by : Mohammad Ehteram
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.
Book Synopsis Mine Planning and Equipment Selection 2000 by : T.N. Michalakopoulos
Download or read book Mine Planning and Equipment Selection 2000 written by T.N. Michalakopoulos and published by CRC Press. This book was released on 2000-01-01 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text looks at mine planning and equipment and covers topics such as: design and planning of surface and underground mines; geotechnical stability in surface and underground mines; and mining and the environment.
Book Synopsis Mine Planning and Equipment Selection by :
Download or read book Mine Planning and Equipment Selection written by and published by . This book was released on 2000 with total page 1002 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Neural-network Modelling of Placer Ore Grade Spatial Variability by : Jinchuan Ke
Download or read book Neural-network Modelling of Placer Ore Grade Spatial Variability written by Jinchuan Ke and published by . This book was released on 2002 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditional geostatistical methods have been used in ore reserve estimation for decades. Research in the last two decades or so has added a number of other statistical methodologies for ore reserve estimation procedures. Recent advances in neural networks have provided a new approach to solve this problem. This thesis is focused on the Neural-network modeling for the estimation of placer ore reserve. Due to the spatial variability, multiple dimensional inputs and very noisy drill hole sample data from the selected region, it requires that the neural-network be organized in a multiple-layers to handle the non-linearity and hidden slabs for smoothing the predicted results. Various neural-network architectures are investigated and the Back-propagation is selected for modeling the ore reserve estimation problem. Sensitivity analysis is performed for the following parameters: the type of neural-network architecture, number of hidden layers and hidden neurons, type of activation functions, learning rate and momentum factors, input pattern schedule, weight updated, and so on. The influences of these parameters on the predicted output are analyzed in details and the optimal parameters are determined. To investigate the accuracy and promise of neural network modeling as a tool for ore reserve estimation, the ore grade and tonnage of Neural-network output is compared with those estimated by geostatistical methods under various cut-off grades. In addition, the overall performance is also validated by the analysis of R-squared (R2), Root-Mean-Squared (RMS), and the comparison between predicted values and 'actual' values. As the final part of this study, the optimized Neural Network was used to esimate the distribution of placer gold grade and volume of gold resource in offshore Nome. The predicted results for all the mining blocks in the lease area are validated by checking the values of RMS, R2, and Scatter plots. The estimated gold grades are also presented as contour maps for visualization"--Leaf iii.
Book Synopsis Geochemical Anomaly and Mineral Prospectivity Mapping in GIS by : E.J.M. Carranza
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
Book Synopsis Mineral Resource Estimation by : Mario E. Rossi
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.
Book Synopsis Applications of Artificial Intelligence in Mining and Geotechnical Engineering by : Hoang Nguyen
Download or read book Applications of Artificial Intelligence in Mining and Geotechnical Engineering written by Hoang Nguyen and published by Elsevier. This book was released on 2023-11-20 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering provides recent advances in mining, geotechnical and geoengineering, as well as applications of artificial intelligence in these areas. It serves as the first book on applications of artificial intelligence in mining, geotechnical and geoengineering, providing an opportunity for researchers, scholars, engineers, practitioners and data scientists from all over the world to understand current developments and applications. Topics covered include slopes, open-pit mines, quarries, shafts, tunnels, caverns, underground mines, metro systems, dams and hydro-electric stations, geothermal energy, petroleum engineering, and radioactive waste disposal. In the geotechnical and geoengineering aspects, topics of specific interest include, but are not limited to, foundation, dam, tunneling, geohazard, geoenvironmental and petroleum engineering, rock mechanics, geotechnical engineering, soil mechanics and foundation engineering, civil engineering, hydraulic engineering, petroleum engineering, engineering geology, etc. Guides readers through the process of gathering, processing, and analyzing datasets specifically tailored for mining, geotechnical, and engineering challenges. Examines the evolution and practical implementation of artificial intelligence models in predicting, forecasting, and optimizing solutions for mining, geotechnical, and engineering problems. Offers cutting-edge methodologies to address the most demanding and complex issues encountered in the fields of mining, geotechnical studies, and engineering.
Book Synopsis Predictive Performance of Machine Learning Algorithms for Ore Reserve Estimation in Sparse and Imprecise Data by : Sridhar Dutta
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.
Book Synopsis Advances in Machine Learning Research and Application: 2012 Edition by :
Download or read book Advances in Machine Learning Research and Application: 2012 Edition written by and published by ScholarlyEditions. This book was released on 2012-12-26 with total page 1934 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Machine Learning. The editors have built Advances in Machine Learning Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Machine Learning in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Machine Learning Research and Application / 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Book Synopsis Computer Applications in Resource Estimation by : G. Gaal
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.
Book Synopsis Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards by :
Download or read book Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards written by and published by . This book was released on 2003 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theses on any subject submitted by the academic libraries in the UK and Ireland.
Book Synopsis SME Mining Engineering Handbook, Third Edition by : Peter Darling
Download or read book SME Mining Engineering Handbook, Third Edition written by Peter Darling and published by SME. This book was released on 2011 with total page 1912 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third edition of the SME Mining Engineering Handbook reaffirms its international reputation as "the handbook of choice" for today's practicing mining engineer. It distills the body of knowledge that characterizes mining engineering as a disciplinary field and has subsequently helped to inspire and inform generations of mining professionals.Virtually all of the information is original content, representing the latest information from more than 250 internationally recognized mining industry experts. Within the handbook's 115 thought-provoking chapters are current topics relevant to today's mining professional: Analyzing how the mining and minerals industry will develop over the medium and long term--why such changes are inevitable, what this will mean in terms of challenges, and how they could be managed Explaining the mechanics associated with the multifaceted world of mine and mineral economics, from the decisions associated with how best to finance a single piece of high-value equipment to the long-term cash-flow issues associated with mine planning at a mature operation Describing the recent and ongoing technical initiatives and engineering developments in relation to robotics, automation, acid rock drainage, block caving optimization, or process dewatering methods Examining in detail the methods and equipment available to achieve efficient, predictable, and safe rock breaking, whether employing a tunnel boring machine for development work, mineral extraction using a mobile miner, or cast blasting at a surface coal operation Identifying the salient points that dictate which is the safest, most efficient, and most versatile extraction method to employ, as well as describing in detail how each alternative is engineered Discussing the impacts that social and environmental issues have on mining from the pre-exploration phase to end-of-mine issues and beyond, and how to manage these two increasingly important factors to the benefit of both the mining companies and other stakeholders
Book Synopsis Journal of the South African Institute of Mining and Metallurgy by : South African Institute of Mining and Metallurgy
Download or read book Journal of the South African Institute of Mining and Metallurgy written by South African Institute of Mining and Metallurgy and published by . This book was released on 2005 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essentials of Mineral Exploration and Evaluation by : S. M. Gandhi
Download or read book Essentials of Mineral Exploration and Evaluation written by S. M. Gandhi and published by Elsevier. This book was released on 2016-05-10 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Mineral Exploration and Evaluation offers a thorough overview of methods used in mineral exploration campaigns, evaluation, reporting and economic assessment processes. Fully illustrated to cover the state-of-the-art exploration techniques and evaluation of mineral assets being practiced globally, this up-to-date reference offers balanced coverage of the latest knowledge and current global trends in successful mineral exploration and evaluation. From mineral deposits, to remote sensing, to sampling and analysis, Essentials of Mineral Exploration and Evaluation offers an extensive look at this rapidly changing field. Covers the complete spectrum of all aspects of ore deposits and mining them, providing a "one-stop shop" for experts and students Presents the most up-to-date information on developments and methods in all areas of mineral exploration Includes chapters on application of GIS, statistics, and geostatistics in mineral exploration and evaluation Includes case studies to enhance practical application of concepts
Book Synopsis Advanced Analytics in Mining Engineering by : Ali Soofastaei
Download or read book Advanced Analytics in Mining Engineering written by Ali Soofastaei and published by Springer Nature. This book was released on 2022-02-23 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.
