UID:
almahu_9948025730402882
Format:
1 online resource (489 p.)
Edition:
1st ed.
ISBN:
1-281-02541-0
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9786611025410
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0-08-052565-2
Content:
Intelligent systems are required to enhance the capacities being made available to us by the internet and other computer based technologies. The theory necessary to help providing solutions to difficult problems in the construction of intelligent systems are discussed. In particular, attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of a linguistic nature. Various methodologies to manage such information are discussed. Among these are the probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks.〈p
Note:
Description based upon print version of record.
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Cover; Contents; Preface; Part 1: Perception-based Information Processing; Chapter 1. Toward a Perception-Based Theory of Probabilistic Reasoning with Imprecise Probabilities; Part 2: Representing Knowledge; Chapter 2. Rough Set Uncertainty in an Object Oriented Data Model; Chapter 3. On the Representation of Fuzzy Spatial Relations in Robot Maps; Chapter 4. Fuzzy ""Between"" Operators in the Framework of Fuzzy Orderings; Chapter 5. A Step towards Conceptually Improving Takagi-Sugeno's Approximation; Chapter 6. Combining Heterogeneous Information in Group Decision Making
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Chapter 7. Function Approximation by Fuzzy Rough SetsPart 3: Retrieving Information; Chapter 8. Query Aggregation Reflecting Domain-knowledge; Chapter 9. Modelling of Fuzzy and Uncertain Spatio-Temporal Information in Databases: A Constraint-based Approach; Chapter 10. A General Framework for Meta-search based on Query-weighting and Numerical Aggregation Operators; Chapter 11. On the Comparison of Aggregates over Fuzzy Sets; Chapter 12. Towards an Intelligent Text Categorization for Web Resources: An Implementation; Part 4: Reasoning; Chapter 13. Prototype Based Reasoning and Fuzzy Modeling
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Chapter 14. Gradual Handling of Contradiction in Argumentation FrameworksChapter 15. Coherent Conditional Probability as a Tool for Default Reasoning; Chapter 16. Detecting Conflict-Free Assumption-Based Knowledge Bases; Part 5: Uncertainty; Chapter 17. Theory of Belief Functions: History and Prospects; Chapter 18. Towards Another Logical Interpretation of Theory of Evidence and a New Combination Rule; Chapter 19. Uncertainty, Type-2 Fuzzy Sets, and Footprints of Uncertainty; Chapter 20. Rough Sets, Bayes' Theorem and Flow Graphs; Chapter 21. Belief Revision as Combinatorial Optimization
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Chapter 22. Showing why Measures of Quantified Beliefs are Belief FunctionsChapter 23. Extension of Coherent Lower Previsions to Unbounded Random Variables; Part 6: Learning and Mining; Chapter 24. Clustering of Proximity Data using Belief Functions; Chapter 25. A Hierarchical Linguistic Clustering Algorithm for Prototype Induction; Chapter 26. A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems; Chapter 27. Mining Implication-Based Fuzzy Association Rules in Databases
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Chapter 28. Learning Graphical Models by Extending Optimal Spanning TreesChapter 29. Clustering Belief Functions Based on Attracting and Conflicting Metalevel Evidence; Part 7: Foundations; Chapter 30. Models and Submodels of Fuzzy Theories; Chapter 31. Numerical Representations of Fuzzy Relational Systems; Chapter 32. Normal Forms for Fuzzy Relations and Their Contribution to Universal Approximation; Chapter 33. Associative Operators Based on t-Norms and t-Conorms; Part 8: Applications; Chapter 34. Non-Analytical Approaches to Model-Based Fault Detection and Isolation
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Chapter 35. A Hybrid Fuzzy-Fractal Approach for Time Series Analysis and Prediction and its Applications to Plant Monitoring
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English
Additional Edition:
ISBN 0-444-51379-5
Language:
English
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