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Literature review of methods for representing uncertainty

Literature review of methods for representing uncertainty
Author: Enrico Zio
Publisher: FonCSI
Total Pages: 61
Release: 2013-03-01
Genre: Technology & Engineering
ISBN:

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This document provides a critical review of different frameworks for uncertainty analysis, in a risk analysis context : classical probabilistic analysis, imprecise probability (interval analysis), probability bound analysis, evidence theory, and possibility theory. The driver of the critical analysis is the decision-making process and the need to feed it with representative information derived from the risk assessment, to robustly support the decision. Technical details of the different frameworks are exposed only to the extent necessary to analyze and judge how these contribute to the communication of risk and the representation of the associated uncertainties to decision-makers, in the typical settings of high-consequence risk analysis of complex systems with limited knowledge on their behaviour.


Risk Analysis

Risk Analysis
Author: Enrico Zio
Publisher:
Total Pages: 49
Release: 2013
Genre:
ISBN:

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Uncertainty in Risk Assessment

Uncertainty in Risk Assessment
Author: Terje Aven
Publisher: John Wiley & Sons
Total Pages: 152
Release: 2013-12-17
Genre: Mathematics
ISBN: 1118763068

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Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.


Uncertainty

Uncertainty
Author: Millett Granger Morgan
Publisher: Cambridge University Press
Total Pages: 376
Release: 1990-08-31
Genre: Psychology
ISBN: 113993581X

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The authors explain the ways in which uncertainty is an important factor in the problems of risk and policy analysis. This book outlines the source and nature of uncertainty, discusses techniques for obtaining and using expert judgment, and reviews a variety of simple and advanced methods for analyzing uncertainty.


Science and Judgment in Risk Assessment

Science and Judgment in Risk Assessment
Author: National Research Council
Publisher: National Academies Press
Total Pages: 668
Release: 1994-01-01
Genre: Science
ISBN: 030904894X

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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.


Uncertainty characterization in risk analysis for decision-making practice

Uncertainty characterization in risk analysis for decision-making practice
Author: Enrico Zio
Publisher: FonCSI
Total Pages: 63
Release: 2012-05-01
Genre: Technology & Engineering
ISBN:

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This document provides an overview of sources of uncertainty in probabilistic risk analysis. For each phase of the risk analysis process (system modeling, hazard identification, estimation of the probability and consequences of accident sequences, risk evaluation), the authors describe and classify the types of uncertainty that can arise. The document provides : a description of the risk assessment process, as used in hazardous industries such as nuclear power and offshore oil and gas extraction ; a classification of sources of uncertainty (both epistemic and aleatory) and a description of techniques for uncertainty representation ; a description of the different steps involved in a Probabilistic Risk Assessement (PRA) or Quantitative Risk Assessment (QRA), and an analysis of the types of uncertainty that can affect each of these steps ; annexes giving an overview of a number of tools used during probabilistic risk assessment, including the HAZID technique, fault trees and event tree analysis.


Bayesian Reinforcement Learning

Bayesian Reinforcement Learning
Author: Mohammad Ghavamzadeh
Publisher:
Total Pages: 146
Release: 2015-11-18
Genre: Computers
ISBN: 9781680830880

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Bayesian methods for machine learning have been widely investigated, yielding principled methods for incorporating prior information into inference algorithms. This monograph provides the reader with an in-depth review of the role of Bayesian methods for the reinforcement learning (RL) paradigm. The major incentives for incorporating Bayesian reasoning in RL are that it provides an elegant approach to action-selection (exploration/exploitation) as a function of the uncertainty in learning, and it provides a machinery to incorporate prior knowledge into the algorithms. Bayesian Reinforcement Learning: A Survey first discusses models and methods for Bayesian inference in the simple single-step Bandit model. It then reviews the extensive recent literature on Bayesian methods for model-based RL, where prior information can be expressed on the parameters of the Markov model. It also presents Bayesian methods for model-free RL, where priors are expressed over the value function or policy class. Bayesian Reinforcement Learning: A Survey is a comprehensive reference for students and researchers with an interest in Bayesian RL algorithms and their theoretical and empirical properties.


Review of the Department of Homeland Security's Approach to Risk Analysis

Review of the Department of Homeland Security's Approach to Risk Analysis
Author: National Research Council
Publisher: National Academies Press
Total Pages: 160
Release: 2010-10-10
Genre: Political Science
ISBN: 0309159245

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The events of September 11, 2001 changed perceptions, rearranged national priorities, and produced significant new government entities, including the U.S. Department of Homeland Security (DHS) created in 2003. While the principal mission of DHS is to lead efforts to secure the nation against those forces that wish to do harm, the department also has responsibilities in regard to preparation for and response to other hazards and disasters, such as floods, earthquakes, and other "natural" disasters. Whether in the context of preparedness, response or recovery from terrorism, illegal entry to the country, or natural disasters, DHS is committed to processes and methods that feature risk assessment as a critical component for making better-informed decisions. Review of the Department of Homeland Security's Approach to Risk Analysis explores how DHS is building its capabilities in risk analysis to inform decision making. The department uses risk analysis to inform decisions ranging from high-level policy choices to fine-scale protocols that guide the minute-by-minute actions of DHS employees. Although DHS is responsible for mitigating a range of threats, natural disasters, and pandemics, its risk analysis efforts are weighted heavily toward terrorism. In addition to assessing the capability of DHS risk analysis methods to support decision-making, the book evaluates the quality of the current approach to estimating risk and discusses how to improve current risk analysis procedures. Review of the Department of Homeland Security's Approach to Risk Analysis recommends that DHS continue to build its integrated risk management framework. It also suggests that the department improve the way models are developed and used and follow time-tested scientific practices, among other recommendations.


Sensitivity & Uncertainty Analysis, Volume 1

Sensitivity & Uncertainty Analysis, Volume 1
Author: Dan G. Cacuci
Publisher: CRC Press
Total Pages: 304
Release: 2003-05-28
Genre: Mathematics
ISBN: 0203498798

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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


Uncertainty propagation and importance measure assessment

Uncertainty propagation and importance measure assessment
Author: Enrico Zio
Publisher: FonCSI
Total Pages: 69
Release: 2013-12-14
Genre: Technology & Engineering
ISBN:

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The authors investigate the effects that different representations of epistemic uncertainty have on practical risk assessment problems. Two different application problems are considered: 1. the estimation of component importance measures in the presence of epistemic uncertainties; 2. the propagation of uncertainties through a risk flooding model. The focus is on the epistemic uncertainty affecting the parameters of the models that describe the components’ failures due to incomplete knowledge of their values. This epistemic uncertainty is represented using probability distributions when sufficient data is available for statistical analysis, and by possibility distributions when the information available to define the parameters’ values comes from experts, in the form of imprecise quantitative statements or judgments. Three case studies of increasing complexity are presented:  a pedagogical example of importance measure assessment on a three-component system from the literature;  assessment of importance measures for the auxiliary feed water system of a nuclear pressurized water reactor;  an application in environmental modelling, with an analysis of uncertainty propagation in a hydraulic model for the risk-based design of a flood protection dike.