Subsurface Environmental Modelling Between Science and Policy, Scheer Dirk, Class Holger, Flemisch Bernd
Автор: Crockett, Robin (university Of Northampton) Название: A Primer on Fourier Analysis for the Geosciences ISBN: 1316600246 ISBN-13(EAN): 9781316600245 Издательство: Cambridge Academ Рейтинг: Цена: 6019.00 р. Наличие на складе: Поставка под заказ.
Описание: An intuitive introduction to basic Fourier theory, with an emphasis on geoscience applications. Numerous worked examples from R are used to illustrate the theory, making this an ideal practical guide for graduate students and researchers who are using time-series analysis to quantify periodic features in geoscience data.
Описание: IoT-based Computational Modeling for Next Generation Agro-ecosystems: Research Issues, Emerging Trends and Challenges.- An IoT-Based Time Constrained Spectrum Trading in Wireless Communication for Tertiary Market.- 5G NB-IoT Enabled Smart Green Agriculture 4.0: A Survey.- Drones for Intelligent Agricultural Management.- Multi-Modal Sensor Nodes in Experimental Scalable Agricultural IoT Application Scenarios.- Design Architecture of Intelligent Agri-Infrastructure Incorporating IoT and Cloud: Link Budget and Socio-Economic Impact.- Remote Sensing and Soil Quality.- Enabling IoT Wireless Technologies in Sustainable Livestock Farming toward Agriculture 4.0.
Автор: Scheer Dirk, Class Holger, Flemisch Bernd Название: Subsurface Environmental Modelling Between Science and Policy ISBN: 3030511774 ISBN-13(EAN): 9783030511777 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a broad overview of essential features of subsurface environmental modelling at the science-policy interface, offering insights into the potential challenges in the field of subsurface flow and transport, as well as the corresponding computational modelling and its impact on the area of policy- and decision-making.
Автор: Bhattacharya Shuvajit Название: A Primer on Machine Learning in Subsurface Geosciences ISBN: 3030717674 ISBN-13(EAN): 9783030717674 Издательство: Springer Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences.
Автор: P. Schulz; Rainer Helmig Название: Multiphase Flow and Transport Processes in the Subsurface ISBN: 3642645453 ISBN-13(EAN): 9783642645457 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: One important precondition for modeling multiphase flow and transport processes in the hydrosystem "subsurface" is the general formulation of a model.
Автор: Caers Название: Quantifying Uncertainty in Subsurface Systems ISBN: 1119325838 ISBN-13(EAN): 9781119325833 Издательство: Wiley Рейтинг: Цена: 25019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge.
Volume highlights include:
A multi-disciplinary treatment of uncertainty quantification
Case studies with actual data that will appeal to methodology developers
A Bayesian evidential learning framework that reduces computation and modeling time
Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians.
Read the Editors' Vox: https: //eos.org/editors-vox/quantifying-uncertainty-about-earths-resources
Reviews, The Leading Edge, SEG, May 2020
The subsurface medium created by geologic processes is not always well understood. The data we collect in an attempt to characterize the subsurface can be incomplete and inaccurate. However, if we understand the uncertainty of our data and the models we generate from them, we can make better decisions regarding the management of subsurface resources. Modeling and managing subsurface resources, and properly characterizing and understanding the uncertainties, requires the integration of a variety of scientific and engineering disciplines.
Five case studies are outlined in the introductory chapter, which are used to demonstrate various methods throughout the book. The second chapter introduces the basic notions in decision analysis. Uncertainty quantification is only relevant within the decision framework used. Models alone do not quantify uncertainty, but do allow the determination of key variables that influence models and decisions. Next, an overview of the various data science methods relevant to uncertainty quantification in the subsurface is provided. Sensitivity analysis is then covered, specifically Monte Carlo-based sensitivity analysis. The next three chapters develop the Bayesian approach to uncertainty quantification, and this is the focus of the book.
All of this is brought together in Chapter 8, which describes a solution regarding quantifying the uncertainties for each of the problems presented in the first chapter. The authors admit that it is not the only solution. No single solution fits all problems of uncertainty quantification. The results in this chapter allow the reader to see the previously described methods applied and how choices influence models and decisions. The final two chapters discuss various software components necessary to implement the strategies presented in the book and challenges faced in the future of uncertainty quantification.
The book uses a number of relevant subsurface problems to explore the various aspects of uncertainty quantification. Understanding uncertainty, and how it affects modeling and decision outcomes, is not always straightforward. However, it is necessary in order to make good, consistent decisions. The book is not an easy read. Some portions require good mathematical understanding of the underlying principles. However, the book is well documented and organized. I would say that is not a good book for a beginner, but it is a good resource for someone to get a grounding to go further into the subject. I appreciate the authors putting together this book on a complex problem that is important to our industry.
Описание: Dedicated to the pioneering Prof. Peter Young, this volume features cutting-edge research in systems and control subjects he has covered in 45 years of research, including system identification, time-series analysis, environmetric modelling and system design.
Автор: Robin Crockett Название: A Primer on Fourier Analysis for the Geosciences ISBN: 1107142881 ISBN-13(EAN): 9781107142886 Издательство: Cambridge Academ Рейтинг: Цена: 7920.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An intuitive introduction to basic Fourier theory, with an emphasis on geoscience applications. Numerous worked examples from R are used to illustrate the theory, making this an ideal practical guide for graduate students and researchers who are using time-series analysis to quantify periodic features in geoscience data.
In recent decades, science has experienced a revolutionary shift. The development and extensive application of computer modelling and simulation has transformed the knowledge‐making practices of scientific fields as diverse as astro‐physics, genetics, robotics and demography. This epistemic transformation has brought with it a simultaneous heightening of political relevance and a renewal of international policy agendas, raising crucial questions about the nature and application of simulation knowledges throughout public policy.
Through a diverse range of case studies, spanning over a century of theoretical and practical developments in the atmospheric and environmental sciences, this book argues that computer modelling and simulation have substantially changed scientific and cultural practices and shaped the emergence of novel 'cultures of prediction'.
Making an innovative, interdisciplinary contribution to understanding the impact of computer modelling on research practice, institutional configurations and broader cultures, this volume will be essential reading for anyone interested in the past, present and future of climate change and the environmental sciences.
Описание: Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a holistic, conceptual and quantitative framework for Environmental Health Modelling in space-time.
Описание: The discovery and development of new computational methods have expanded the capabilities and uses of simulations. With agent-based models, the applications of computer simulations are significantly enhanced.Multi-Agent-Based Simulations Applied to Biological and Environmental Systems is a pivotal reference source for the latest research on the implementation of autonomous agents in computer simulation paradigms. Featuring extensive coverage on relevant applications, such as biodiversity conservation, pollution reduction, and environmental risk assessment, this publication is an ideal source for researchers, academics, engineers, practitioners, and professionals seeking material on various issues surrounding the use of agent-based simulations.
Автор: Mihailovi? Dragutin Название: Time and Methods in Environmental Interfaces Modelling ISBN: 0444639187 ISBN-13(EAN): 9780444639189 Издательство: Elsevier Science Рейтинг: Цена: 15748.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Time and Methods in Environmental Interfaces Modelling: Personal Insights considers the use of time in environmental interfaces modeling and introduce new methods, from the global scale (e.g. climate modeling) to the micro scale (e.g. cell and nanotubes modeling), which primarily arise from the personal research insights of the authors.
As the field of environmental science requires the application of new fundamental approaches that can lead to a better understanding of environmental phenomena, this book helps necessitate new approaches in modeling, including category theory, that follow new achievements in physics, mathematics, biology, and chemistry.
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