Scenario Logic and Probabilistic Management of Risk in Business and Engineering [electronic resource] /
Solojentsev, Evgueni D.author.
The book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It covers the methodological and theoretical basis of risk management at the design, test, and operation stages of economic, banking, and engineering systems with groups of incompatible events (GIE). It considers the risk LP-models in classification, investment, management of companies, bribes and corruption, analysis of risk and efficiency of social and economical processes, and management of development. Key features of this Second Edition: -Five new chapters -Treatment of the basic principles of the modern risk LP theory (the LP-calculus, the LP-methods and the risk LP-theory with GIE) using uniform methodology and terminology with a practical orientation towards both engineering and economics, for the first time in book form -Clear definitions and notations, revised sections and chapters, an extended list of references, and a new subject index -More than a hundred illustrations and tables which motivate the presentation Specialists in risk management in economics, banking and business, as well as graduates and post-graduates in economics and engineering, will benefit from this book.
Description based upon print version of record.
Includes bibliographical references (p. 435-443) and index.
Management and Risk -- The Human Being And Risks -- Principles of Risk Management in Design -- Risk Management at Debugging Tests -- Risk Management In Operation On Basis Of Monitoring -- Risk Management on Dangerous Plant -- Transparency of Methods for Estimation -- Bases of Logic and Probabilistic Calculus -- Lp Modeling And Analysis Of Risk In -- Automated Structural and Logical Modeling -- Logical And Probabilistic Theory Of Risk With Groups Of Incompatible Events -- Identification of Risk Lp-Models with Groups of Incompatible Events -- Lp Analysis of Risk in Systems with Groups of Incompatible Events -- Software For Assessment Analysis And Management Of Risk -- Lp Model of Credit Risk for Natural -- Lp Model of Credit Risk for Juridical -- Scenario Logic And Probabilistic Risk Models Of Bribes -- Lp Model of Security Portfolio Risk -- Risk Lp Models of Quality and Efficiency -- Lp Models Of Company Management -- Lp Models of Frauds and Interaction of Companies -- The Formal Lp Theory Of Non Success Risk -- Training Course Modeling Estimation and Analysis of Risks in Economics.
The book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It covers the methodological and theoretical basis of risk management at the design, test, and operation stages of economic, banking, and engineering systems with groups of incompatible events (GIE). It considers the risk LP-models in classification, investment, management of companies, bribes and corruption, analysis of risk and efficiency of social and economical processes, and management of development. Key features of this Second Edition: -Five new chapters -Treatment of the basic principles of the modern risk LP theory (the LP-calculus, the LP-methods and the risk LP-theory with GIE) using uniform methodology and terminology with a practical orientation towards both engineering and economics, for the first time in book form -Clear definitions and notations, revised sections and chapters, an extended list of references, and a new subject index -More than a hundred illustrations and tables which motivate the presentation Specialists in risk management in economics, banking and business, as well as graduates and post-graduates in economics and engineering, will benefit from this book.
Business.
Management science.
Economics, Mathematical .
Econometrics.
Mathematical logic.
Probabilities.
Business and Management, general.
Quantitative Finance.
Econometrics.
Mathematical Logic and Foundations.
Probability Theory and Stochastic Processes.
Springer optimization and its applications