Soft methods for integrated uncertainty modelling
This edited volume is the proceedings of the 2006 International Conference on Soft Methods in Probability and Statistics (SMPS 2006) hosted by the Artificial Intelligence Group at the University of Bristol, between 5-7 September 2006. This is the third of a series of biennial conferences organized i...
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| Άλλοι συγγραφείς: | , , , , , , |
|---|---|
| Μορφή: | Livre numérique |
| Γλώσσα: | Anglais |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Έκδοση: | 1st ed. 2006. |
| Σειρά: | Advances in Intelligent and Soft Computing
37 |
| Διαθέσιμο Online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Σημείωση: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Soft Methods for Integrated Uncertainty Modelling, Texte imprimé, 9783540347767 • Soft Methods for Integrated Uncertainty Modelling, Texte imprimé, 9783540825173 |
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| 245 | 0 | 0 | |a Soft methods for integrated uncertainty modelling |c edited by Jonathan Lawry, Enrique Miranda, Alberto Bugarin, Shoumei Li, Maria Angeles Gil, Przemys aw Grzegorzewski, Olgierd Hyrniewicz. |
| 250 | |a 1st ed. 2006. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Advances in Intelligent and Soft Computing |v 37 |x 1867-5670 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Keynote Papers Generalized Theory of Uncertainty (GTU) Principal Concepts and Ideas Reasoning with Vague Probability Assessments Soft Methods in Earth Systems Engineering Statistical Data Processing under Interval Uncertainty: Algorithms and Computational Complexity Soft Methods in Statistics and Random Information Systems On Testing Fuzzy Independence Variance Decomposition of Fuzzy Random Variables Fuzzy Histograms and Density Estimation Graded Stochastic Dominance as a Tool for Ranking the Elements of a Poset On Neyman-Pearson Lemma for Crisp, Random and Fuzzy Hypotheses Fuzzy Probability Distributions Induced by Fuzzy Random Vectors On the Identifiability of TSK Additive Fuzzy Rule-Based Models An Asymptotic Test for Symmetry of Random Variables Based on Fuzzy Tools Exploratory Analysis of Random Variables Based on Fuzzifications A Method to Simulate Fuzzy Random Variables Friedman s Test for Ambiguous and Missing Data Probability of Imprecisely-Valued Random Elements with Applications Measure-Free Martingales with Application to Classical Martingales A Note on Random Upper Semicontinuous Functions Optional Sampling Theorem and Representation of Set-Valued Amart On a Choquet Theorem for Random Upper Semicontinuous Functions A General Law of Large Numbers, with Applications Applications and Modelling of Imprecise Operators Fuzzy Production Planning Model for Automobile Seat Assembling Optimal Selection of Proportional Bounding Quantifiers in Linguistic Data Summarization A Linguistic Quantifier Based Aggregation for a Human Consistent Summarization of Time Series Efficient Evaluation of Similarity Quantified Expressions in the Temporal Domain Imprecise Probability Theory Conditional Lower Previsions for Unbounded Random Quantities Extreme Lower Probabilities Equivalence Between Bayesian and Credal Nets on an Updating Problem Varying Parameter in Classification Based on Imprecise Probabilities Comparing Proportions Data with Few Successes A Unified View of Some Representations of Imprecise Probabilities Possibility, Evidence and Interval Methods Estimating an Uncertain Probability Density Theory of Evidence with Imperfect Information Conditional IF-probability On Two Ways for the Probability Theory on IF-sets A Stratification of Possibilistic Partial Explanations Finite Discrete Time Markov Chains with Interval Probabilities Evidence and Compositionality High Level Fuzzy Labels for Vague Concepts Integrated Uncertainty Modelling in Applications Possibilistic Channels for DNA Word Design Transformation of Possibility Functions in a Climate Model of Intermediate Complexity Fuzzy Logic for Stochastic Modeling A CUSUM Control Chart for Fuzzy Quality Data A Fuzzy Synset-Based Hidden Markov Model for Automatic Text Segmentation Applying Fuzzy Measures for Considering Interaction Effects in Fine Root Dispersal Models | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a This edited volume is the proceedings of the 2006 International Conference on Soft Methods in Probability and Statistics (SMPS 2006) hosted by the Artificial Intelligence Group at the University of Bristol, between 5-7 September 2006. This is the third of a series of biennial conferences organized in 2002 by the Systems Research Institute from the Polish Academy of Sciences in Warsaw, and in 2004 by the Department of Statistics and Operational Research at the University of Oviedo in Spain. These conferences provide a forum for discussion and research into the fusion of soft methods with probability and statistics, with the ultimate goal of integrated uncertainty modelling in complex systems involving human factors. In addition to probabilistic factors such as measurement error and other random effects, the modelling process often requires us to make qualitative and subject judgments that cannot easily be translated into precise probability values. Such judgments give rise to a number of different types of uncertainty including; fuzziness if they are based on linguistic information; epistemic uncertainty when their reliability is in question; ignorance when they are insufficient to identify or restrict key modelling parameters; imprecision when parameters and probability distributions can only be estimated within certain bounds. Statistical theory has not traditionally been concerned with modelling uncertainty arising in this manner but soft methods, a range of powerful techniques developed within AI, attempt to address those problems where the encoding of subjective information is unavoidable. These are mathematically sound uncertainty modelling methodologies which are complementary to conventional statistics and probability theory. Therefore, a more realistic modelling process providing decision makers with an accurate reflection of the true current state of our knowledge (and ignorance) requires an integrated framework incorporating both probability theory, statistics and soft methods. This fusion motivates innovative research at the interface between computer science (AI), mathematics and systems engineering | ||
| 700 | 1 | |a Lawry, Jonathan. |4 pbd | |
| 700 | 1 | |a Miranda, Enrique. |4 pbd | |
| 700 | 1 | |a Bugarin, Alberto. |4 pbd | |
| 700 | 1 | |a Gil, María Ángeles. |4 pbd | |
| 700 | 1 | |a Grzegorzewski, Przemysław. |4 pbd | |
| 700 | 1 | |a Hyrniewicz, Olgierd. |4 pbd | |
| 700 | 1 | |a Li, Shoumei. |4 pbd | |
| 776 | 0 | |t Soft Methods for Integrated Uncertainty Modelling |b Texte imprimé |z 9783540347767 | |
| 776 | 0 | |t Soft Methods for Integrated Uncertainty Modelling |b Texte imprimé |z 9783540825173 | |
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