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100301s2008 gw | s |||| 0|eng d |
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|a 9783540447924
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024 |
7 |
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|a 10.1007/978-3-540-44792-4
|2 doi
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040 |
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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245 |
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|a Classic Works of the Dempster-Shafer Theory of Belief Functions /
|c edited by Ronald R. Yager, Liping Liu.
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250 |
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|a 1st ed. 2008.
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260 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2008.
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300 |
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|a XIX, 806 p. 81 illus. :
|b online resource.
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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490 |
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|a Studies in Fuzziness and Soft Computing,
|v 219
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505 |
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|a Classic Works of the Dempster-Shafer Theory of Belief Functions: An Introduction -- New Methods for Reasoning Towards Posterior Distributions Based on Sample Data -- Upper and Lower Probabilities Induced by a Multivalued Mapping -- A Generalization of Bayesian Inference -- On Random Sets and Belief Functions -- Non-Additive Probabilities in the Work of Bernoulli and Lambert -- Allocations of Probability -- Computational Methods for A Mathematical Theory of Evidence -- Constructive Probability -- Belief Functions and Parametric Models -- Entropy and Specificity in a Mathematical Theory of Evidence -- A Method for Managing Evidential Reasoning in a Hierarchical Hypothesis Space -- Languages and Designs for Probability Judgment -- A Set-Theoretic View of Belief Functions -- Weights of Evidence and Internal Conflict for Support Functions -- A Framework for Evidential-Reasoning Systems -- Epistemic Logics, Probability, and the Calculus of Evidence -- Implementing Dempster’s Rule for Hierarchical Evidence -- Some Characterizations of Lower Probabilities and Other Monotone Capacities through the use of Möbius Inversion -- Axioms for Probability and Belief-Function Propagation -- Generalizing the Dempster–Shafer Theory to Fuzzy Sets -- Bayesian Updating and Belief Functions -- Belief-Function Formulas for Audit Risk -- Decision Making Under Dempster–Shafer Uncertainties -- Belief Functions: The Disjunctive Rule of Combination and the Generalized Bayesian Theorem -- Representation of Evidence by Hints -- Combining the Results of Several Neural Network Classifiers -- The Transferable Belief Model -- A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory -- Logicist Statistics II: Inference.
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650 |
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|a Applied mathematics.
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650 |
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|a Engineering mathematics.
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650 |
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|a Artificial intelligence.
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650 |
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|a Game theory.
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650 |
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|a Economic theory.
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650 |
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4 |
|a Mathematical and Computational Engineering.
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650 |
2 |
4 |
|a Artificial Intelligence.
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650 |
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4 |
|a Game Theory, Economics, Social and Behav. Sciences.
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650 |
2 |
4 |
|a Economic Theory/Quantitative Economics/Mathematical Methods.
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700 |
1 |
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|a Yager, Ronald R.
|e editor.
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700 |
1 |
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|a Liu, Liping.
|e editor.
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
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|t Springer eBooks
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