Elicitation of Expert Opinions for Uncertainty and Risks
Auteur : Ayyub Bilal M.
Experts, despite their importance and value, can be double-edged swords. They can make valuable contributions from their deep base of knowledge, but those contributions may also contain their own biases and pet theories. Therefore, selecting experts, eliciting their opinions, and aggregating their opinions must be performed and handled carefully, with full recognition of the uncertainties inherent in those opinions.
Elicitation of Expert Opinions for Uncertainty and Risks illuminates those uncertainties and builds a foundation of philosophy, background, methods, and guidelines that helps its readers effectively execute the elicitation process. Based on the first-hand experiences of the author, the book is filled with illustrations, examples, case studies, and applications that demonstrate not only the methods and successes of expert opinion elicitation, but also its pitfalls and failures.
Studies show that in the future, analysts, engineers, and scientists will need to solve ever more complex problems and reach decisions with limited resources. This will lead to an increased reliance on the proper treatment of uncertainty and on the use of expert opinions. Elicitation of Expert Opinions for Uncertainty and Risks will help prepare you to better understand knowledge and ignorance, to successfully elicit expert opinions, to select appropriate expressions of those opinions, and to use various methods to model and aggregate opinions.
Date de parution : 06-2001
Ouvrage de 302 p.
15.6x23.4 cm
Thème d’Elicitation of Expert Opinions for Uncertainty and Risks :
Mots-clés :
Expert Opinion Elicitation; expertopinion; Fuzzy Set; aggregate; Expertopinion Elicitation; failure; Cumulative Distribution Function; probabilities; Basic Assignment; occurrence; Membership Function; combining; Monotone Measures; fuzzy; High High High High High; set; Fuzzy Number; blind; Rough Sets; ignorance; Trapezoidal Fuzzy Membership Functions; Source System; Fuzzy Failure; Fuzzy Relation; Triangular Fuzzy Number; Combining Expert Opinions; Rough Set Approximation; Fuzzy Arithmetic; Crisp Sets; Aggregating Expert Opinions; Accident Probability; Work Breakdown Structure; Blind Ignorance; Delphi Method; Residential Structural Types