Machine Learning for Subsurface Characterization PDF Download
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Author: Siddharth Misra
Publisher: Gulf Professional Publishing
ISBN: 0128177373
Category : Technology & Engineering
Languages : en
Pages : 442
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Book Description
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. - Learn from 13 practical case studies using field, laboratory, and simulation data - Become knowledgeable with data science and analytics terminology relevant to subsurface characterization - Learn frameworks, concepts, and methods important for the engineer's and geoscientist's toolbox needed to support
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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Book Description
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Author: J. Nathan Kutz
Publisher: SIAM
ISBN: 1611974496
Category : Science
Languages : en
Pages : 241
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Book Description
Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Author: Yasmin Murad
Publisher: Frontiers Media SA
ISBN: 2832509177
Category : Technology & Engineering
Languages : en
Pages : 134
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Book Description
Author: Zhishen Wu
Publisher: CRC Press
ISBN: 1000057941
Category : Architecture
Languages : en
Pages : 245
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Book Description
With rapid urbanization in developing countries and the emergence of smart systems and integrated intelligent devices, the new generation of infrastructure will be smarter and more efficient. However, due to natural and anthropomorphic hazards, as well as the adverse impact of climate change, civil infrastructure systems are increasingly vulnerable. Therefore, future-proofing and designing resilience into infrastructure is one of the biggest challenges facing the industry and governments in all developing and industrialized societies. This book provides a comprehensive overview of infrastructure resiliency, new developments in this emerging field and its scopes, including ecology and sustainability, and the challenges involved in building more resilient civil infrastructure systems. Moreover, it introduces a strategic roadmap for effective and efficient methods needed for modeling, designing, and assessing resiliency. Features: Includes contributions from internationally recognized scholars in the emerging field of infrastructure resilience. Covers a broad range of topics in infrastructure resilience such as disaster assessment, civil infrastructure and lifeline systems, natural hazard mitigation, and seismic protection. Includes practical global case studies and leading-edge research from several countries. Presents an interdisciplinary approach in addressing the challenges in the emerging field of infrastructure resilience Resilience of Critical Infrastructure Systems: Emerging Developments and Future Challenges serves as a valuable resource for practicing professionals, researchers, and advanced students seeking practical, forward-looking guidance.
Author: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833
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Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Author: Anthony J. G. Hey
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 292
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Book Description
Foreword. A transformed scientific method. Earth and environment. Health and wellbeing. Scientific infrastructure. Scholarly communication.
Author: Alma Y Alanis
Publisher: Academic Press
ISBN: 0128182474
Category : Science
Languages : en
Pages : 176
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Book Description
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.
Author: Wei Song
Publisher: Frontiers Media SA
ISBN: 2889663809
Category : Technology & Engineering
Languages : en
Pages : 213
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Book Description
Author: Dashun Wang
Publisher: Cambridge University Press
ISBN: 1108492665
Category : Computers
Languages : en
Pages : 315
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Book Description
This is the first comprehensive overview of the exciting field of the 'science of science'. With anecdotes and detailed, easy-to-follow explanations of the research, this book is accessible to all scientists, policy makers, and administrators with an interest in the wider scientific enterprise.
Author:
Publisher: SPA Risk LLC
ISBN:
Category :
Languages : en
Pages : 216
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Book Description
