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Risk Modeling, Assessment, and Management 4th edition [Kõva köide]

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Series edited by (George Mason University), Edited by (Center for Risk Management of Engineering Systems, University of Virginia, Charlottesville)
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Risk Modeling, Assessment, and Management 4th editionSuurem pilt
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Püsilink: https://www.kriso.ee/db/9781119017981.html
Märksõnad:
Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management

This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research.

The fourth edition of Risk Modeling, Assessment, and Management features:









Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmers Dilemma formulated and solved using a deterministic linear model Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application



Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.
Preface to the Fourth Edition ix
The Companion Website xv
Acknowledgments xvii
Part I Fundamentals of Risk Modeling, Assessment, and Management
1(226)
1 The Art and Science of Systems and Risk Analysis
3(38)
1.1 Introduction
3(1)
1.2 Systems Engineering
4(10)
1.3 Risk Assessment and Management
14(12)
1.4 Concept Road Map
26(9)
1.5 Epilogue
35(6)
References
35(6)
2 The Role of Modeling in the Definition and Quantification of the Risk Function
41(28)
2.1 Introduction
41(2)
2.2 The Risk Assessment and Management Process: Historical Perspectives
43(2)
2.3 Information, Intelligence, and Models
45(2)
2.4 The Building Blocks of Mathematical Models
47(4)
2.5 On the Complex Definition of Risk, Vulnerability, and Resilience: A Systems-Based Approach
51(5)
2.6 On the Definition of Vulnerabilities in Measuring Risks to Systems
56(1)
2.7 On the Definition of Resilience in Measuring Risk to Systems
57(3)
2.8 On the Complex Quantification of Risk to Systems
60(9)
References
65(4)
3 Identifying Risk through Hierarchical Holographic Modeling and Its Derivatives
69(46)
3.1 Hierarchical Aspects
69(1)
3.2 Hierarchical Overlapping Coordination
70(3)
3.3 HHM
73(3)
3.4 HHM and the Theory of Scenario Structuring
76(3)
3.5 Adaptive Multiplayer HHM Game
79(1)
3.6 Water Resources System
80(3)
3.7 Sustainable Development
83(3)
3.8 HHM in a System Acquisition Project
86(4)
3.9 Software Acquisition
90(4)
3.10 Hardening the Water Supply Infrastructure
94(4)
3.11 Risk Assessment and Management for Support of Operations other than War
98(5)
3.12 Automated Highway System
103(5)
3.13 Food-Poisoning Scenarios
108(7)
References
113(2)
4 Modeling and Decision Analysis
115(40)
4.1 Introduction
115(1)
4.2 Decision Rules Under Uncertainty
116(2)
4.3 Decision Trees
118(4)
4.4 Decision Matrix
122(2)
4.5 The Fractile Method
124(3)
4.6 Triangular Distribution
127(1)
4.7 Influence Diagrams
128(4)
4.8 Population Dynamic Models
132(7)
4.9 PSM
139(5)
4.10 Example Problems
144(11)
References
152(3)
5 Multiobjective Trade-Off Analysis
155(24)
5.1 Introduction
155(2)
5.2 Examples of Multiple Environmental Objectives
157(2)
5.3 The Surrogate Worth Trade-Off Method
159(7)
5.4 Characterizing a Proper Noninferior Solution
166(2)
5.5 The SWT Method and the Utility Function Approach
168(4)
5.6 Example Problems
172(5)
5.7 Summary
177(2)
References
178(1)
6 Defining Uncertainty and Sensitivity Analysis
179(32)
6.1 Introduction
179(1)
6.2 Sensitivity, Responsivity, Stability, and Irreversibility
180(2)
6.3 Uncertainties Due to Errors in Modeling
182(1)
6.4 Characterization of Modeling Errors
183(2)
6.5 Uncertainty Taxonomy
185(11)
6.6 The USIM
196(3)
6.7 Formulation of the Multiobjective Optimization Problem
199(5)
6.8 A Robust Algorithm of the USIM
204(3)
6.9 Integration of the USIM with Parameter Optimization at the Design Stage
207(2)
6.10 Conclusions
209(2)
References
209(2)
7 Risk Filtering, Ranking, and Management
211(1)
71 Introduction
211(16)
7.2 Past Efforts in Risk Filtering and Ranking
212(1)
7.3 RFRM: A Methodological Framework
213(7)
7.4 Case Study: An OOTW
220(4)
7.5 Summary
224(3)
References
224(3)
Part II Advances in Risk Modeling, Assessment, and Management
227(390)
8 Risk of Extreme Events and the Fallacy of the Expected Value
229(30)
8.1 Introduction
229(1)
8.2 Risk of Extreme Events
230(2)
8.3 The Fallacy of the Expected Value
232(1)
8.4 The PMRM
233(3)
8.5 General Formulation of the PMRM
236(2)
8.6 Summary of the PMRM
238(1)
8.7 Illustrative Example
239(1)
8.8 Analysis of Dam Failure and Extreme Flood through the PMRM
240(3)
8.9 Example Problems
243(14)
8.10 Summary
257(2)
References
257(2)
9 Multiobjective Decision-Tree Analysis
259(36)
9.1 Introduction
259(2)
9.2 Methodological Approach
261(18)
9.3 Differences between SODT and MODT
279(2)
9.4 Summary
281(1)
9.5 Example Problems
282(13)
References
293(2)
10 Multiobjective Risk Impact Analysis Method
295(34)
10.1 Introduction
295(1)
10.2 Impact Analysis
296(1)
10.3 The Multiobjective, Multistage Impact Analysis Method: An Overview
297(1)
10.4 Combining the PMRM and the MMIAM
298(6)
10.5 Relating Multiobjective Decision Trees to the MRIAM
304(9)
10.6 Example Problems
313(12)
10.7 Epilogue
325(4)
References
326(3)
11 Statistics of Extremes: Extension of the PMRM
329(42)
11.1 A Review of the Partitioned Multiobjective Risk Method
329(4)
11.2 Statistics of Extremes
333(5)
11.3 Incorporating the Statistics of Extremes into the PMRM
338(6)
11.4 Sensitivity Analysis of the Approximation of f4(·)
344(6)
11.5 Generalized Quantification of Risk of Extreme Events
350(6)
11.6 Summary
356(1)
11.7 Example Problems
357(14)
References
368(3)
12 Systems-Based Guiding Principles for Risk Modeling, Planning, Assessment, Management, and Communication
371(18)
12.1 Introduction
371(1)
12.2 The Journey: The Guiding Principles in the Broader Context of the Emerging Next Generation Developed by the Federal Aviation Administration
372(17)
References
387(2)
13 Fault Trees
389(34)
13.1 Introduction
389(2)
13.2 Basic Fault-Tree Analysis
391(1)
13.3 Reliability and Fault-Tree Analysis
392(5)
13.4 Minimal Cut Sets
397(3)
13.5 The DARE Using Fault Trees
400(3)
13.6 Extreme Events in Fault Tree Analysis
403(2)
13.7 An Example Problem Based on a Case Study
405(4)
13.8 Failure Mode and Effects Analysis and Failure Mode, Effects, and Criticality Analysis
409(2)
13.9 Event Trees
411(3)
13.10 Example Problems
414(9)
References
420(3)
14 Multiobjective Statistical Method
423(16)
14.1 Introduction
423(1)
14.2 Mathematical Formulation of the Interior Drainage Problem
424(1)
14.3 Formulation of the Optimization Problem
424(1)
14.4 The MSM: Step-by-Step
425(2)
14.5 The SWT Method
427(1)
14.6 Multiple Objectives
428(1)
14.7 Applying the MSM
429(3)
14.8 Example Problems
432(7)
References
438(1)
15 Principles and Guidelines for Project Risk Management
439(34)
15.1 Introduction
439(1)
15.2 Definitions and Principles of Project Risk Management
440(3)
15.3 Project Risk Management Methods
443(7)
15.4 Aircraft Development Example
450(4)
15.5 Quantitative Risk Assessment and Management of Software Acquisition
454(4)
15.6 Critical Factors That Affect Software Nontechnical Risk
458(2)
15.7 Basis for Variances in Cost Estimation
460(1)
15.8 Discrete Dynamic Modeling
461(8)
15.9 Summary
469(4)
References
469(4)
16 Modeling Complex Systems of Systems with Phantom System Models
473(20)
16.1 Introduction
473(1)
16.2 What Have We Learned from Other Contributors?
474(2)
16.3 The Centrality of the States of the System in Modeling and in Risk Analysis
476(1)
16.4 The Centrality of Time in Modeling Multidimensional Risk, Uncertainty, and Benefits
477(1)
16.5 Extension of HHM to PSM
478(2)
16.6 PSM and Meta-modeling
480(6)
16.7 PSM Laboratory
486(2)
16.8 Summary
488(5)
References
489(4)
17 Adaptive Two-Player Hierarchical Holographic Modeling Game for Counterterrorism Intelligence Analysis
493(18)
17.1 Introduction
493(1)
17.2 Bayes' Theorem
494(1)
17.3 Modeling the Multiple Perspectives of Complex Systems
495(4)
17.4 Adaptive Two-Player HHM Game: Terrorist Networks versus Homeland Protection
499(3)
17.5 The Building Blocks of Mathematical Models and the Centrality of State Variables in Intelligence Analysis
502(2)
17.6 Hierarchical Adaptive Two-Player HHM Game
504(1)
17.7 Collaborative Computing Support for Adaptive Two-Player HHM Games
505(2)
17.8 Summary
507(4)
References
508(3)
18 Inoperability Input--Output Model and Its Derivatives for Interdependent Infrastructure Sectors
511(32)
18.1 Overview
511(1)
18.2 Background: The Original Leontief Input--Output Model
512(1)
18.3 Inoperability Input--Output Model
513(3)
18.4 Regimes of Recovery
516(1)
18.5 Supporting Databases for IIM Analysis
517(1)
18.6 National and Regional Databases for IIM Analysis
518(4)
18.7 RIMS II
522(1)
18.8 Development of the IIM and Its Extensions
523(4)
18.9 The Dynamic IIM
527(3)
18.10 Practical Uses of the IIM
530(3)
18.11 Uncertainty IIM
533(3)
18.12 Example Problems
536(3)
18.13 Summary
539(4)
References
540(3)
19 Case Studies
543(74)
19.1 A Risk-Based Input--Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout
543(15)
19.2 Systemic Valuation of Strategic Preparedness Through Applying the IIM with Lessons Learned from Hurricane Katrina
558(11)
19.3 Ex Post Analysis Using the IIM of the September 11, 2001, Attack on the United States
569(6)
19.4 Risk Modeling, Assessment, and Management of Lahar Flow Threat
575(12)
19.5 The Statistics of Extreme Events and 6-Sigma Capability
587(6)
19.6 Sequential Pareto-Optimal Decisions Made During Emergent Complex Systems of Systems: An Application to the FAA NextGen
593(24)
References
612(5)
Appendix: Optimization Techniques
617(50)
A.1 Introduction to Modeling and Optimization
617(38)
A.2 Bayesian Analysis and the Prediction of Chemical Carcinogenicity
655(2)
A.3 The Farmer's Dilemma: Linear Model and Duality
657(7)
A.4 Standard Normal Probability Table
664(3)
References
665(2)
Author Index 667(6)
Subject Index 673
YACOV Y. HAIMES, PhD, is the Lawrence R. Quarles Professor at the School of Engineering and Applied Science, University of Virginia, USA, and is a member of the Systems and Information Engineering faculty and the Civil and Environmental Engineering faculty. He is the Founding Director (1987) of the university-wide Center for Risk Management of Engineering Systems. On the faculty of Case Western Reserve University, USA, for 17 years, he was the Chair of the Systems Engineering Department, and Director of the Center for Large-Scale Systems and Policy Analysis.