Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Mathematical logic --- Ensembles flous. --- Systèmes flous. --- Fuzzy sets. --- Fuzzy systems. --- Fuzzy sets --- Fuzzy systems --- Ensembles flous --- Systèmes flous --- ELSEVIER-B EPUB-LIV-FT --- 681.3*I51 --- 681.3*I51 Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Systems, Fuzzy --- System analysis --- Fuzzy logic --- Sets, Fuzzy --- Fuzzy mathematics --- Set theory

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Expert systems (Computer science). --- Fuzzy sets.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Spatial information is pervaded by uncertainty. Indeed, geographical data is often obtained by an imperfect interpretation of remote sensing images, while people attach ill-defined or ambiguous labels to places and their properties. As another example, medical images are often the result of measurements by imprecise sensors (e.g. MRI scans). Moreover, by processing spatial information in real-world applications, additional uncertainty is introduced, e.g. due to the use of interpolation/extrapolation techniques or to conflicts that are detected in an information fusion step. To the best of our knowledge, this book presents the first overview of spatial uncertainty which goes beyond the setting of geographical information systems. Uncertainty issues are especially addressed from a representation and reasoning point of view. In particular, the book consists of 14 chapters, which are clustered around three central topics. The first of these topics is about the uncertainty in meaning of linguistic descriptions of spatial scenes. Second, the issue of reasoning about spatial relations and dealing with inconsistency in information merging is studied. Finally, interpolation and prediction of spatial phenomena are investigated, both at the methodological level and from an application-oriented perspective. The concept of uncertainty by itself is understood in a broad sense, including both quantitative and more qualitative approaches, dealing with variability, epistemic uncertainty, as well as with vagueness of terms.

Geospatial data --- Fuzzy mathematics --- Errors, Scientific --- Geography --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Earth & Environmental Sciences --- Applied Mathematics --- Geography-General --- Civil Engineering --- Mathematical models --- Soft computing. --- Fuzzy sets. --- Sets, Fuzzy --- Engineering. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Set theory --- Cognitive computing --- Electronic data processing --- Computational intelligence --- Mathematical and Computational Engineering. --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Uncertainty (Information theory) --- Artificial intelligence --- Incertitude (Théorie de l'information) --- Intelligence artificielle --- Congresses. --- Congrès --- Computer Science --- Mechanical Engineering - General --- Mechanical Engineering --- Engineering & Applied Sciences --- Information Technology --- Artificial Intelligence --- Business. --- Management science. --- Mathematical logic. --- Artificial intelligence. --- Business and Management. --- Business and Management, general. --- Artificial Intelligence (incl. Robotics). --- Mathematical Logic and Formal Languages. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Trade --- Economics --- Commerce --- Industrial management --- Computer science. --- Artificial Intelligence. --- Informatics --- Science

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Fuzzy Sets, Logics and Reasoning about Knowledge reports recent results concerning the genuinely logical aspects of fuzzy sets in relation to algebraic considerations, knowledge representation and commonsense reasoning. It takes a state-of-the-art look at multiple-valued and fuzzy set-based logics, in an artificial intelligence perspective. The papers, all of which are written by leading contributors in their respective fields, are grouped into four sections. The first section presents a panorama of many-valued logics in connection with fuzzy sets. The second explores algebraic foundations, with an emphasis on MV algebras. The third is devoted to approximate reasoning methods and similarity-based reasoning. The fourth explores connections between fuzzy knowledge representation, especially possibilistic logic and prioritized knowledge bases. Readership: Scholars and graduate students in logic, algebra, knowledge representation, and formal aspects of artificial intelligence.

Fuzzy logic. --- Fuzzy sets. --- Many-valued logic.