Download or read book Random Explorations written by Gregory F. Lawler and published by American Mathematical Society. This book was released on 2022-12-06 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: The title “Random Explorations” has two meanings. First, a few topics of advanced probability are deeply explored. Second, there is a recurring theme of analyzing a random object by exploring a random path. This book is an outgrowth of lectures by the author in the University of Chicago Research Experiences for Undergraduate (REU) program in 2020. The idea of the course was to expose advanced undergraduates to ideas in probability research. The book begins with Markov chains with an emphasis on transient or killed chains that have finite Green's function. This function, and its inverse called the Laplacian, is discussed next to relate two objects that arise in statistical physics, the loop-erased random walk (LERW) and the uniform spanning tree (UST). A modern approach is used including loop measures and soups. Understanding these approaches as the system size goes to infinity requires a deep understanding of the simple random walk so that is studied next, followed by a look at the infinite LERW and UST. Another model, the Gaussian free field (GFF), is introduced and related to loop measure. The emphasis in the book is on discrete models, but the final chapter gives an introduction to the continuous objects: Brownian motion, Brownian loop measures and soups, Schramm-Loewner evolution (SLE), and the continuous Gaussian free field. A number of exercises scattered throughout the text will help a serious reader gain better understanding of the material.

Download or read book Random Processes for Engineers written by Bruce Hajek and published by Cambridge University Press. This book was released on 2015-03-12 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms. Key topics covered include: • Calculus of random processes in linear systems • Kalman and Wiener filtering • Hidden Markov models for statistical inference • The estimation maximization (EM) algorithm • An introduction to martingales and concentration inequalities. Understanding of the key concepts is reinforced through over 100 worked examples and 300 thoroughly tested homework problems (half of which are solved in detail at the end of the book).

Download or read book Explorations in Monte Carlo Methods written by Ronald W. Shonkwiler and published by Springer Science & Business Media. This book was released on 2009-08-11 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems. Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. Each chapter ends with a large collection of problems illustrating and directing the material. This book is suitable as a textbook for students of engineering and the sciences, as well as mathematics.

Download or read book Into a Deeper Understanding of Evolutionary Computing Exploration Exploitation and Parameter Control written by Abdul Hanif Abdul Halim and published by Springer Nature. This book was released on with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Common Core Math Explorations written by Jerry Burkhart and published by Taylor & Francis. This book was released on 2021-09-03 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stretch your students' mathematical imaginations to their limits as they solve challenging real-world and mathematical problems that extend concepts from the Common Core State Standards for Mathematics in Advanced Common Core Math Explorations: Probability and Statistics. Students will learn powerful mathematical ideas about data and chance as they make sense of real-world situations from science, sports, and everyday life. Each activity comes with extensive teacher support, including student handouts, discussion guides, detailed solutions, and suggestions for extending the investigations. Grades 5-8

Download or read book DATA EXPLORATION AND DATA PREPARATION PHASE written by Dr. Raja Sarath Kumar Boddu and published by Xoffencerpublication. This book was released on 2021-09-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of the last decade, the amount of data with which one must deal has skyrocketed to levels that are difficult to fathom, while at the same time, the cost of storing data has steadily decreased. Private firms and research organizations collect terabytes of data about their customers' interactions, commerce, and social media, as well as sensors from devices such as mobile phones and vehicles. This data is used for a variety of purposes, including marketing and advertising. Figuring out how to make sense of all this data is one of the most difficult challenges of our day. The analysis of large amounts of data comes into play at this point. Big Data Analytics entails, for the most part, the gathering of data from a variety of sources, the management of this data in such a manner that it can be utilized by analysts, and the delivery of data products that are beneficial to the organization's business.

Download or read book Some Statistical Problems of Uranium Exploration written by M. R. Mickey and published by . This book was released on 1954 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mining Intelligence and Knowledge Exploration written by Rajendra Prasath and published by Springer. This book was released on 2013-12-16 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2013, held in Tamil Nadu, India on December 2013. The 82 papers presented were carefully reviewed and selected from 334 submissions. The papers cover the topics such as feature selection, classification, clustering, image processing, network security, speech processing, machine learning, information retrieval, recommender systems, natural language processing, language, cognition and computation and other certain problems in dynamical systems.

Download or read book Proceedings of the International Field Exploration and Development Conference 2018 written by Jia'en Lin and published by Springer Nature. This book was released on 2019-10-02 with total page 2063 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers from the 8th International Field Exploration and Development Conference (IFEDC 2018) and addresses a broad range of topics, including: Reservoir Surveillance and Management, Reservoir Evaluation and Dynamic Description, Reservoir Production Stimulation and EOR, Ultra-Tight Reservoirs, Unconventional Oil and Gas Resources Technology, Oil and Gas Well Production Testing, and Geomechanics. In brief, the papers introduce readers to upstream technologies used in oil & gas development, the main principles of the process, and various related design technologies. The conference not only provided a platform to exchange experiences, but also promoted the advancement of scientific research in oil & gas exploration and production. The book is chiefly intended for industry experts, professors, researchers, senior engineers, and enterprise managers.

Download or read book Strategies for Optimizing Petroleum Exploration written by Lev Knoring and published by Elsevier. This book was released on 1999-05-14 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a valuable guide to appraise and develop petroleum resources. Geology largely determines exploration policy. This book analyzes the strategic connection between the two and shows how to improve decision making on appraising and developing petroleum resources. It examines and describes the internal patterns in finding oil and gas deposits and outlines a process to evaluate the resources. The book also provides a means for long-term reserve accrual forecasting and evaluation. It uses mathematical modeling as a method to evaluate the initial potential of an oil and gas region as well as a way to forecast future reserves. These models improve the reliability and validity of exploration forecasts and estimates. Strategies for Optimizing Petroleum Exploration helps petroleum engineers and explorationists focus and improve their reserve assessment and decision making. This book shows how to develop and appraise petroleum resources.

Download or read book Exploration and Analysis of DNA Microarray and Other High Dimensional Data written by Dhammika Amaratunga and published by John Wiley & Sons. This book was released on 2014-01-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “...extremely well written...a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.

Download or read book Data Cleaning and Exploration with Machine Learning written by Michael Walker and published by Packt Publishing Ltd. This book was released on 2022-08-26 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore supercharged machine learning techniques to take care of your data laundry loads Key FeaturesLearn how to prepare data for machine learning processesUnderstand which algorithms are based on prediction objectives and the properties of the dataExplore how to interpret and evaluate the results from machine learningBook Description Many individuals who know how to run machine learning algorithms do not have a good sense of the statistical assumptions they make and how to match the properties of the data to the algorithm for the best results. As you start with this book, models are carefully chosen to help you grasp the underlying data, including in-feature importance and correlation, and the distribution of features and targets. The first two parts of the book introduce you to techniques for preparing data for ML algorithms, without being bashful about using some ML techniques for data cleaning, including anomaly detection and feature selection. The book then helps you apply that knowledge to a wide variety of ML tasks. You'll gain an understanding of popular supervised and unsupervised algorithms, how to prepare data for them, and how to evaluate them. Next, you'll build models and understand the relationships in your data, as well as perform cleaning and exploration tasks with that data. You'll make quick progress in studying the distribution of variables, identifying anomalies, and examining bivariate relationships, as you focus more on the accuracy of predictions in this book. By the end of this book, you'll be able to deal with complex data problems using unsupervised ML algorithms like principal component analysis and k-means clustering. What you will learnExplore essential data cleaning and exploration techniques to be used before running the most popular machine learning algorithmsUnderstand how to perform preprocessing and feature selection, and how to set up the data for testing and validationModel continuous targets with supervised learning algorithmsModel binary and multiclass targets with supervised learning algorithmsExecute clustering and dimension reduction with unsupervised learning algorithmsUnderstand how to use regression trees to model a continuous targetWho this book is for This book is for professional data scientists, particularly those in the first few years of their career, or more experienced analysts who are relatively new to machine learning. Readers should have prior knowledge of concepts in statistics typically taught in an undergraduate introductory course as well as beginner-level experience in manipulating data programmatically.

Download or read book Soft Computing and Intelligent Data Analysis in Oil Exploration written by M. Nikravesh and published by Elsevier. This book was released on 2003-04-22 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

Download or read book An Exploration of Dynamical Systems and Chaos written by John H. Argyris and published by Springer. This book was released on 2015-04-24 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is conceived as a comprehensive and detailed text-book on non-linear dynamical systems with particular emphasis on the exploration of chaotic phenomena. The self-contained introductory presentation is addressed both to those who wish to study the physics of chaotic systems and non-linear dynamics intensively as well as those who are curious to learn more about the fascinating world of chaotic phenomena. Basic concepts like Poincaré section, iterated mappings, Hamiltonian chaos and KAM theory, strange attractors, fractal dimensions, Lyapunov exponents, bifurcation theory, self-similarity and renormalisation and transitions to chaos are thoroughly explained. To facilitate comprehension, mathematical concepts and tools are introduced in short sub-sections. The text is supported by numerous computer experiments and a multitude of graphical illustrations and colour plates emphasising the geometrical and topological characteristics of the underlying dynamics. This volume is a completely revised and enlarged second edition which comprises recently obtained research results of topical interest, and has been extended to include a new section on the basic concepts of probability theory. A completely new chapter on fully developed turbulence presents the successes of chaos theory, its limitations as well as future trends in the development of complex spatio-temporal structures. "This book will be of valuable help for my lectures" Hermann Haken, Stuttgart "This text-book should not be missing in any introductory lecture on non-linear systems and deterministic chaos" Wolfgang Kinzel, Würzburg “This well written book represents a comprehensive treatise on dynamical systems. It may serve as reference book for the whole field of nonlinear and chaotic systems and reports in a unique way on scientific developments of recent decades as well as important applications.” Joachim Peinke, Institute of Physics, Carl-von-Ossietzky University Oldenburg, Germany

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

Download or read book Data Mining and Exploration written by Chong Ho Alex Yu and published by CRC Press. This book was released on 2022-10-27 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications.

Download or read book Knowledge Exploration in Life Science Informatics written by Jesús A. López and published by Springer. This book was released on 2005-01-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.