Download or read book Science and Judgment in Risk Assessment written by National Research Council and published by National Academies Press. This book was released on 1994-01-01 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: The public depends on competent risk assessment from the federal government and the scientific community to grapple with the threat of pollution. When risk reports turn out to be overblownâ€"or when risks are overlookedâ€"public skepticism abounds. This comprehensive and readable book explores how the U.S. Environmental Protection Agency (EPA) can improve its risk assessment practices, with a focus on implementation of the 1990 Clean Air Act Amendments. With a wealth of detailed information, pertinent examples, and revealing analysis, the volume explores the "default option" and other basic concepts. It offers two views of EPA operations: The first examines how EPA currently assesses exposure to hazardous air pollutants, evaluates the toxicity of a substance, and characterizes the risk to the public. The second, more holistic, view explores how EPA can improve in several critical areas of risk assessment by focusing on cross-cutting themes and incorporating more scientific judgment. This comprehensive volume will be important to the EPA and other agencies, risk managers, environmental advocates, scientists, faculty, students, and concerned individuals.

Download or read book Water Resource Systems Planning and Management written by Daniel P. Loucks and published by Springer. This book was released on 2017-03-02 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY-NC 4.0 license. This revised, updated textbook presents a systems approach to the planning, management, and operation of water resources infrastructure in the environment. Previously published in 2005 by UNESCO and Deltares (Delft Hydraulics at the time), this new edition, written again with contributions from Jery R. Stedinger, Jozef P. M. Dijkman, and Monique T. Villars, is aimed equally at students and professionals. It introduces readers to the concept of viewing issues involving water resources as a system of multiple interacting components and scales. It offers guidelines for initiating and carrying out water resource system planning and management projects. It introduces alternative optimization, simulation, and statistical methods useful for project identification, design, siting, operation and evaluation and for studying post-planning issues. The authors cover both basin-wide and urban water issues and present ways of identifying and evaluating alternatives for addressing multiple-purpose and multi-objective water quantity and quality management challenges. Reinforced with cases studies, exercises, and media supplements throughout, the text is ideal for upper-level undergraduate and graduate courses in water resource planning and management as well as for practicing planners and engineers in the field.

Download or read book Methods and Guidelines for Effective Model Calibration written by Mary Catherine Hill and published by . This book was released on 1998 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-07-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

Download or read book Model Calibration and Parameter Estimation written by Ne-Zheng Sun and published by Springer. This book was released on 2015-07-01 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can be used as a reference for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for professionals such as petroleum engineers, mining engineers, chemists, mechanical engineers, biologists, biology and medical engineering, applied mathematicians, and others who perform mathematical modeling.

Download or read book Real Time Optimization written by Dominique Bonvin and published by MDPI. This book was released on 2018-07-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Real-Time Optimization" that was published in Processes

Download or read book Working with Dynamic Crop Models written by Daniel Wallach and published by Academic Press. This book was released on 2013-11-25 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines. - 50% new content – 100% reviewed and updated - Clearly explains practical application of the methods presented, including R language examples - Presents real-life examples of core crop modeling methods, and ones that are translatable to dynamic system models in other fields

Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.

Download or read book Scaling and Uncertainty Analysis in Ecology written by Jianguo Wu and published by Springer Science & Business Media. This book was released on 2006-07-02 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book of its kind – explicitly considering uncertainty and error analysis as an integral part of scaling. The book draws together a series of important case studies to provide a comprehensive review and synthesis of the most recent concepts, theories and methods in scaling and uncertainty analysis. It includes case studies illustrating how scaling and uncertainty analysis are being conducted in ecology and environmental science.

Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.

Download or read book Integrated Population Models written by Michael Schaub and published by Academic Press. This book was released on 2021-11-12 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrated Population Models: Theory and Ecological Applications with R and JAGS is the first book on integrated population models, which constitute a powerful framework for combining multiple data sets from the population and the individual levels to estimate demographic parameters, and population size and trends. These models identify drivers of population dynamics and forecast the composition and trajectory of a population. Written by two population ecologists with expertise on integrated population modeling, this book provides a comprehensive synthesis of the relevant theory of integrated population models with an extensive overview of practical applications, using Bayesian methods by means of case studies. The book contains fully-documented, complete code for fitting all models in the free software, R and JAGS. It also includes all required code for pre- and post-model-fitting analysis. Integrated Population Models is an invaluable reference for researchers and practitioners involved in population analysis, and for graduate-level students in ecology, conservation biology, wildlife management, and related fields. The text is ideal for self-study and advanced graduate-level courses. - Offers practical and accessible ecological applications of IPMs (integrated population models) - Provides full documentation of analyzed code in the Bayesian framework - Written and structured for an easy approach to the subject, especially for non-statisticians

Download or read book Modeling Uncertainty in the Earth Sciences written by Jef Caers and published by John Wiley & Sons. This book was released on 2011-05-25 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; large complexity and dimensionality; computation power; costs of 'engineering' the Earth; uncertainty in the modeling and decision process. Focusing on reliable and practical methods this book provides an invaluable primer for the complex area of decision making with uncertainty in the Earth Sciences.

Download or read book Uncertainty Analysis in Engineering and Sciences Fuzzy Logic Statistics and Neural Network Approach written by Bilal Ayyub and published by Springer Science & Business Media. This book was released on 1997-10-31 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Download or read book Sensitivity Uncertainty Analysis Volume 1 written by Dan G. Cacuci and published by CRC Press. This book was released on 2003-05-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable investigative scientific tools in their own right. While most techniques used for these analyses are well documented, there has yet to appear a systematic treatment of the method based

Download or read book Practical Protein Crystallography written by Duncan E. McRee and published by Elsevier. This book was released on 1999-09-27 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for easy use by both beginning and experienced protein crystallographers, the second edition of Practical Protein Crystallography is an essential handbook for any scientist interested in solving a protein structure. The book includes examples of actual experiments and data, electron density maps, and computer methods. This second edition has new material covering CCP4, SHELX, cryocrystallography, MAD and automated fitting. - In-depth coverage of every aspect of crystallography - Coverage of the small details that can make or break projects - Strongly application-oriented - Exceptionally well illustrated - Simple and easy-to-follow robust methods - Tutorials with actual data available on the Web - Useful for a broad spectrum of scientists

Download or read book Inverse Problem Theory and Methods for Model Parameter Estimation written by Albert Tarantola and published by SIAM. This book was released on 2005-01-01 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the prediction of observations is a forward problem, the use of actual observations to infer the properties of a model is an inverse problem. Inverse problems are difficult because they may not have a unique solution. The description of uncertainties plays a central role in the theory, which is based on probability theory. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, and many of the arguments are heuristic.

Download or read book Uncertainty Analysis and Reservoir Modeling written by Y. Zee Ma and published by AAPG. This book was released on 2011-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: