00737nam2 22002171i 450 990002247600403321000224760FED01000224760(Aleph)000224760FED0100022476020030801d--------km-y0itay50------baPartial and complete reduction ofpyrroles, furans, thiophenes and theirbenzo analogs. Oxford, 1991, v. 8, p.603-633.001000222787Gribble,Gordon W.93007ITUNINARICAUNIMARCBK990002247600403321FFABCPartial and complete reduction ofpyrroles, furans, thiophenes and theirbenzo analogs. Oxford, 1991, v. 8, p.603-633398665UNINAING0100763nam0-22002651i-450-990001246870403321000124687FED01000124687(Aleph)000124687FED0100012468720000920d1984----km-y0itay50------baengGeometry of projective algebraic curvesb y NAMBA MAKOTO.New York [etc.]Marcel Dekker1984x+409cm 16Pure and applied mathematics88Namba,Makoto<1943- >57409ITUNINARICAUNIMARCBK990001246870403321C-8-(886575MA1MA1Geometry of projective algebraic curves381626UNINAING0105307nam 2200637Ia 450 991083009650332120200722233234.01-282-68400-097866126840050-470-61187-10-470-61030-1(CKB)2550000000005840(EBL)477628(SSID)ssj0000354058(PQKBManifestationID)11281489(PQKBTitleCode)TC0000354058(PQKBWorkID)10302399(PQKB)11389758(MiAaPQ)EBC477628(OCoLC)520990369(EXLCZ)99255000000000584020090122d2009 uy 0engur|n|---|||||txtccrDecision-making process Concepts and methods[electronic resource] /edited by Denis Bouyssou ... [et al.]Hoboken, NJ John Wiley & Sons20091 online resource (904 p.)ISTE ;v.135Description based upon print version of record.1-84821-116-3 Includes bibliographical references and index.Decision-making Process; Contents; Preface; Chapter 1. From Decision Theory to Decision-aiding Methodology; 1.1. Introduction; 1.2. History; 1.2.1. Genesis and youth; 1.2.2. Maturity; 1.3. Different decision-aiding approaches; 1.4. The decision-aiding process; 1.4.1. The problem situation; 1.4.2. The problem formulation; 1.4.3. The evaluation model; 1.4.4. The final recommendation; 1.5. Conclusion; 1.6. Acknowledgements; 1.7. Bibliography; Chapter 2. Binary Relations and Preference Modeling; 2.1. Introduction; 2.2. Binary relations; 2.2.1. Definitions; 2.2.2. Properties of a binary relation2.2.3. Graphical representation of a binary relation2.2.4. Matrix representation of a binary relation; 2.2.5. Example; 2.3. Binary relations and preference structures; 2.4. Classical preference structures; 2.4.1. Total order; 2.4.1.1. Definition; 2.4.1.2. Numerical representation; 2.4.2. Weak orders; 2.4.2.1. Definition; 2.4.2.2. Numerical representation; 2.4.3. Classical problems; 2.4.3.1. Choosing on the basis of binary relation; 2.4.3.2. Aggregating preferences; 2.4.3.3. Particular structure of the set of objects; 2.5. Semi-orders and interval orders; 2.5.1. Semi-order; 2.5.1.1. Definition2.5.1.2. Weak order associated with a semi-order2.5.1.3. Matrix representation; 2.5.1.4. Numerical representation; 2.5.2. Interval order; 2.5.2.1. Definition; 2.5.2.2. Weak orders associated with an interval order; 2.5.2.3. Matrix representation; 2.5.2.4. Numerical representation; 2.5.3. Remarks; 2.6. Preference structures with incomparability; 2.6.1. Partial order; 2.6.2. Quasi-order; 2.6.3. Synthesis; 2.7. Conclusion; 2.7.1. Other preference structures; 2.7.2. Other problems; 2.8. Bibliography; Chapter 3. Formal Representations of Uncertainty; 3.1. Introduction3.2. Information: a typology of defects3.2.1. Incompleteness and imprecision; 3.2.2. Uncertainty; 3.2.3. Gradual linguistic information; 3.2.4. Granularity; 3.3. Probability theory; 3.3.1. Frequentists and subjectivists; 3.3.2. Conditional probability; 3.3.3. The unique probability assumption in the subjective setting; 3.4. Incompleteness-tolerant numerical uncertainty theories; 3.4.1. Imprecise probabilities; 3.4.2. Random disjunctive sets and belief functions; 3.4.3. Quantitative possibility theory; 3.4.3.1. Possibility theory and belief functions3.4.3.2. Possibility theory and imprecise probabilities3.4.3.3. Clouds and generalized p-boxes; 3.4.3.4. Possibility-probability transformations; 3.4.4. Possibility theory and non-Bayesian statistics; 3.5. Qualitative uncertainty representations; 3.6. Conditioning in non-additive representations; 3.6.1. Conditional events and qualitative conditioning; 3.6.2. Conditioning for belief functions and imprecise probabilities; 3.7. Fusion of imprecise and uncertain information; 3.7.1. Non-Bayesian probabilistic fusion; 3.7.2. Bayesian probabilistic fusion; 3.7.3. Fusion in possibility theory3.7.4. Fusion of belief functionsThis book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to define a complete understanding of the highly complex processes and outcomes. This book provides the readeISTEDecision support systemsDecision makingMathematical modelsDecision support systems.Decision makingMathematical models.658.4/03658.403Bouyssou D(Denis)731351MiAaPQMiAaPQMiAaPQBOOK9910830096503321Decision-making process3928833UNINA