Rough Sets and Current Trends in Computing 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings /
Rough Sets and Current Trends in Computing 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings / [electronic resource] :
edited by Shusaku Tsumoto, Roman Slowiński, Jan Komorowski, Jerzy W. Grzymala-Busse.
- 1st ed. 2004.
- XX, 860 p. online resource.
- Lecture Notes in Artificial Intelligence, 3066 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 3066 .
Plenary Papers -- Theory -- Logic and Rough Sets -- Granular Computing -- Rough and Fuzzy Relations -- Foundations of Data Mining -- Incomplete Information Systems -- Interestingness -- Multiagents and Information Systems -- Fuzzy Logic and Modeling -- Rough Classification -- Rough Sets and Probabilities -- Variable Precision Rough Set Model -- Spatial Reasoning -- Reduction -- Rule Induction -- Rough Sets and Neural Network -- Clustering -- Data Mining -- Image and Signal Recognition -- Information Retrieval -- Decision Support -- Adaptive and Opminization Methods -- Bioinformatics -- Medical Applications -- Bibliography Project of International Rough Set Society.
In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.
9783540259299
10.1007/b97961 doi
Computer science.
Artificial intelligence.
Machine theory.
Computer vision.
Database management.
Application software.
Theory of Computation.
Artificial Intelligence.
Formal Languages and Automata Theory.
Computer Vision.
Database Management.
Computer and Information Systems Applications.
QA75.5-76.95
004.0151
Plenary Papers -- Theory -- Logic and Rough Sets -- Granular Computing -- Rough and Fuzzy Relations -- Foundations of Data Mining -- Incomplete Information Systems -- Interestingness -- Multiagents and Information Systems -- Fuzzy Logic and Modeling -- Rough Classification -- Rough Sets and Probabilities -- Variable Precision Rough Set Model -- Spatial Reasoning -- Reduction -- Rule Induction -- Rough Sets and Neural Network -- Clustering -- Data Mining -- Image and Signal Recognition -- Information Retrieval -- Decision Support -- Adaptive and Opminization Methods -- Bioinformatics -- Medical Applications -- Bibliography Project of International Rough Set Society.
In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.
9783540259299
10.1007/b97961 doi
Computer science.
Artificial intelligence.
Machine theory.
Computer vision.
Database management.
Application software.
Theory of Computation.
Artificial Intelligence.
Formal Languages and Automata Theory.
Computer Vision.
Database Management.
Computer and Information Systems Applications.
QA75.5-76.95
004.0151