Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation. This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
National Research Council,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Oversight Committee for the Workshop on Statistical Methods in Software Engineering for Defense Systems
Author: National Research Council,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Oversight Committee for the Workshop on Statistical Methods in Software Engineering for Defense Systems
Publisher: National Academies Press
Category: Social Science
Recent rough estimates are that the U.S. Department of Defense (DoD) spends at least $38 billion a year on the research, development, testing, and evaluation of new defense systems; approximately 40 percent of that cost-at least $16 billion-is spent on software development and testing. There is widespread understanding within DoD that the effectiveness of software-intensive defense systems is often hampered by low-quality software as well as increased costs and late delivery of software components. Given the costs involved, even relatively incremental improvements to the software development process for defense systems could represent a large savings in funds. And given the importance of producing defense software that will carry out its intended function, relatively small improvements to the quality of defense software systems would be extremely important to identify. DoD software engineers and test and evaluation officials may not be fully aware of a range of available techniques, because of both the recent development of these techniques and their origination from an orientation somewhat removed from software engineering, i.e., from a statistical perspective. The panel's charge therefore was to convene a workshop to identify statistical software engineering techniques that could have applicability to DoD systems in development.
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen
Author: Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen
Publisher: Academic Press
Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com Glossary of text mining terms provided in the appendix
A practical field reference for mining and mineral engineers that is small enough to carry into the field. With its comprehensive store of charts, graphs, tables, equations, and rules of thumb, this handbook is the essential technical reference for mobile mining professionals.
This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for database administrators who want to use SQL or bolster their understanding of statistics to support data mining and customer relationship management analytics. Each chapter is self-contained, with examples tailored to real business applications. And each analysis technique will be expressed in a mathematical format for coding as either a database query or a Visual Basic procedure using SQL. Chapter contents include formulas, graphs, charts, tables, data mining techniques, and more!
Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. Distinguished contributors who are international experts in aspects of data mining Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions Thorough discussion of data visualization issues blending statistical, human factors, and computational insights
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
Risk and reliability analysis is an area of growing importance in geotechnical engineering, where many variables have to be considered. Statistics, reliability modeling and engineering judgement are employed together to develop risk and decision analyses for civil engineering systems. The resulting engineering models are used to make probabilistic predictions, which are applied to geotechnical problems. Reliability & Statistics in Geotechnical Engineering comprehensively covers the subject of risk and reliability in both practical and research terms * Includes extensive use of case studies * Presents topics not covered elsewhere--spatial variability and stochastic properties of geological materials * No comparable texts available Practicing engineers will find this an essential resource as will graduates in geotechnical engineering programmes.
This volume contains forty-one selected full-text contributions from the Fourth European Conference on Geostatistics for Environmental Applications, geoENV IV, held in Barcelona, Spain, November 2002. The objective of the editors was to compile a set of papers from which the reader could perceive how geostatistics is applied within the environmental sciences. A few selected theoretical contributions are also included. The papers are organized in the following sections: -Air pollution and satellite images, -Ecology and environment, -Hydrogeology, -Climatology and rainfall, -Oceanography, -Soil science, -Methodology. Applications of geostatistics vary from particle matter analysis, land cover classification, space-time ozone mapping, downscaling of precipitation, contaminant transport in the subsurface, aquifer reclamation, analysis of Iberian hare or phytoplankton abundance, coastal current patterns, to soil pollution by heavy metals or dioxins. At the back of the book nineteen posters presented at the congress are included. The combination of full texts and posters provides a picture of the tendencies that can presently be found in Europe regarding the applications of geostatistics for environmentally related problems. Audience: After four editions the geoENV Congress Series has established itself as a 'must' to all scientists working in the field of geostatistics for environmental applications. Each geoENV congress covers the developments which have occurred during the preceding two years, but always with a highly applied focus. It is precisely this focus on the applications to environmental sciences which makes the geoENV volumes unique and of great interest and practical value to geostatisticians working both in academia and in industry.
Hartman (mining engineering, U. of Alabama) and Mutmansky (emeritus, mining engineering, Pennsylvania State U. at University Park) have two primary aims in the presentation of the second edition of their mining textbook: to familiarize readers with the minerals industry and to aid in the selection of the optimal methods for the specified conditions. To achieve those goals they present 14 chapters covering mining and its consequences, prospecting and exploration, development and exploitation, unit operations of mining, surface mine development, mechanical extraction methods, aqueous extraction methods, underground mine development, unsupported and supported methods in underground mining, caving methods, and novel methods and technology. Annotation c. Book News, Inc., Portland, OR (booknews.com).
The return of the congress to North America after 20 years of absence could not have been in a more ideal location. The beauty of Banff and the many offerings of the Rocky Mountains was the perfect background for a week of interesting and innovative discussions on the past, present and future of geostatistics. The congress was well attended with approximately 200 delegates from 19 countries across six continents. There was a broad spectrum of students and seasoned geostatisticians who shared their knowledge in many areas of study including mining, petroleum, and environmental applications. You will find 119 papers in this two volume set. All papers were presented at the congress and have been peer-reviewed. They are grouped by the different sessions that were held in Banff and are in the order of presentation. These papers provide a permanent record of different theoretical perspectives from the last four years. Not all of these ideas will stand the test of time and practice; however, their originality will endure. The practical applications in these proceedings provide nuggets of wisdom to those struggling to apply geostatistics in the best possible way. Students and practitioners will be digging through these papers for many years to come. Oy Leuangthong Clayton V. Deutsch ACKNOWLEDGMENTS We would like to thank the industry sponsors who contributed generously to the overall success and quality of the congress: De Beers Canada Earth Decision Sciences Maptek Chile Ltda. Mira Geoscience Nexen Inc. Petro-Canada Placer Dome Inc.