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Risk Analysis of Complex and Uncertain Systems / by Louis Anthony Cox
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: International Series in Operations Research & Management Science ; 129 | SpringerLink BücherPublisher: Boston, MA : Springer-Verlag US, 2009Description: Online-Ressource (digital)ISBN:- 9780387890142
- 9780387890135
- 658.40301
- 610
- 658.403
- HD30.23
- RA566.3 .C693 2009
Contents:
Summary: 'Tony Cox is among the most active and creative architects and users of quantitative risk analysis. This book is full of interesting equations, conceptual designs and conundrums that characterize QRA and its applications to risk management. Informed by trenchant thinking and perceptive writing, this is a timely resource for the risk analysis community.' Michael R. Greenberg, Professor and Faculty Dean, Edward J. Bloustein School of Planning and Public Policy, Rutgers University 'Tony Cox's impressive book applies both simple and cutting-edge risk models to a variety of fields. It demonstrates creative but tractable ways to model real-world problems of great practical importance regarding biological, engineering, and social risks. This book deserves to become influential and widely read by those seeking practical state-of-the-art methods for risk analysis.' Vicki Bier, Professor, Engineering Physics and Industrial Engineering Director - Center for Human Performance and Risk Analysis, University of Wisconsin-Madison 'Risk analysis is as old as the first cave dweller mulling how to survive winter or woolly mammoths. It remains essential today in our world of accidents, disease, climate change and terrorism. But some say that quantitative risk analysis is too complicated or time-consuming, and that qualitative intuition is a better way to make decisions. In this ambitious and meticulous book, Tony Cox makes the case that quantitative risk analysis is actually the antidote to uncertainty and complexity, superior to other modes of thinking, both practical and effective. Cox raises the bar on a vital debate.' Jonathan B. Wiener, Duke University, and President, Society for Risk Analysis (2008)PPN: PPN: 1648221602Package identifier: Produktsigel: ZDB-2-SBE
Preface; Acknowledgments; Contents; Part I Introduction to Risk Analysis; to 1 Quantitative Risk Assessment Goals and Challenges; The Quantitative Risk Assessment (QRA) Paradigm; Example: A Simple QRA Risk Assessment Model; Example: Explicit QRA Reasoning Can Be Checked and Debated; Against QRA: Toward Concern-Driven Risk Management; Dissatisfactions with QRA; Example: Use of Incorrect Modeling Assumptions in Antimicrobial Risk Assessment; Example: Use of Unvalidated Assumptions in a QRA for BSE (''Mad Cow'' Disease); Toward Less Analytic, More Pluralistic Risk Management
Alternatives to QRA in Recent Policy Making: Some Practical ExamplesConcern-Driven Risk Management; Potential Political Advantages of Concern-Driven Regulatory Risk Management; How Effective Is Judgment-Based Risk Management?; Example: Expert Judgment vs. QRA for Animal Antibiotics; Performance of Individual Judgment vs. Simple Quantitative Models; Performance of Consensus Judgments vs. Simple Quantitative Models; Example: Resistance of Expert Judgments to Contradictory Data; Example: Ignoring Disconfirming Data About BSE Prevalence
Example: Consensus Decision Making Can Waste Valuable Individual InformationHow Effective Can QRA Be?; Summary and Conclusions; to 2 Introduction to Engineering Risk Analysis; Overview of Risk Analysis for Engineered Systems; Example: Unreliable Communication with Reliable Components; Example: Optimal Number of Redundant Components; Example: Optimal Scheduling of Risky Inspections; Using Risk Analysis to Improve Decisions; Hazard Identification: What Should We Worry About?; Example: Fault Tree Calculations for Car Accidents at an Intersection
Structuring Risk Quantification and Displaying Results: Models for Accident Probabilities and ConsequencesExample: Bug-Counting Models of Software Reliability; Example: Risk Management Decision Rules for Dams and Reservoirs; Example: Different Individual Risks for the Same Exceedance Probability Curve; Quantifying Model Components and Inputs; Modeling Interdependent Inputs and Events; Example: Analysis of Accident Precursors; Example: Flight-Crew Alertness; Some Alternatives to Subjective Prior Distributions; Example: Effects of Exposure to Contaminated Soil
Example: The ''Rule of Three'' for Negative EvidenceExample: A Sharp Transition in a Symmetric Multistage Model of Carcinogenesis; Dealing with Model Uncertainty: Bayesian Model Averaging (BMA) and Alternatives; Risk Characterization; Engineering vs. Financial Characterizations of ''Risk'': Why Risk Is Not Variance; Incompatibility of Two Suggested Principles for Financial Risk Analysis; Challenges in Communicating the Results of PRAs; Methods for Risk Management Decision Making; Example: A Bounded-Regret Strategy for Replacing Unreliable Equipment; Methods of Risk Management to Avoid
Game-Theory Models for Risk Management Decision Making
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