SCENARIO LOGIC AND PROBABILISTIC MANAGEMENT OF RISK IN BUSINESS AND ENGINEERING
E.D.Solojentsev
SPRINGER, 2005. Pages - 391 p., Figures - 70; Tables - 40; Refers - 118.
The methodological aspects of the scenario logic and probabilistic (LP) non-success risk management are considered, following from analysis of connections between management and risk, personals and risk, and from study of risk management at stages of design, test and operation of complex systems.
The theoretical bases of the scenario non-success risk LP-management in business and engineering are stated, including LP-calculus, LP-methods, and LP-theory with groups of incompatible events (GIE). Examples of risk LP-models with logical connections OR, AND, NOT, cycles and GIE are given. Methods and algorithms for the scenario risk LP-management in problems of classification, investment and effectiveness are described.
Risk LP-models and results of numerical investigations for credit risks, risk of frauds, security portfolio risk, risk in quality, accuracy, and risk in multi-state system reliability are given. A rather large number of new problems of estimation, analysis and management of risk are considered. In some problems the risk LP-models prove to be showed almost two times more accurate, seven times more robustness and bigger transparency, than other well-known models of risks. Software for risk problems based on LP-methods, LP-theory with GIE and cortege algebra, is described too.
The book is intended for experts and scientists in the area of the risk in business and engineering, in problems of classification, investment and effectiveness, and students and post-graduates.
Contents
Foreword
Introduction
Acronyms and general notations
Chapter 1. Management and Risk
Chapter 2. The human being and risks
Chapter 3. Principles of risk management at design
Chapter 4. Risk management at debugging tests
Chapter 5. Risk management in operation basis on monitoring
Chapter 6. Risk management on dangerous plant
Chapter 7. Bases of logic and probabilistic calculus
Chapter 8. Logic and probabilistic method and risk
Chapter 9. Automated structural and logic modelling
Chapter 10. Foundations of the risk LP-theory with groups of incompatible events
Chapter 11. The risk LP-theory with GIE in the classification problem
Chapter 12. Identification of risk LP-models with groups of incompatible events
Chapter 13. Risk analysis in systems with GIE
Chapter 14. Software for the risk analysis and management
Chapter 15. Risk LP-models in business
Chapter 16. Logic and probabilistic theory of security portfolio risk
Chapter 17. Risk LP-models in engineering
Chapter 18. Risk LP-theory in problems of effectiveness
Conclusion
Bibliography
Subject index
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