Rough Sets and Current Trends in Computing : 4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings / edited by Shusaku Tsumoto, Roman Slowiński, Jan Komorowski, Jerzy W. Grzymala-Busse.

Format:

Book

Contributor:

Tsumoto, Shusaku, 1963- editor.

Słowiński, Roman, editor.

Komorowski, J. (Jan), editor.

Grzymala-Busse, Jerzy W., editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 3066.

Lecture Notes in Artificial Intelligence ; 3066

Language:

English

Subjects (All):

Computers.

Artificial intelligence.

Logic, Symbolic and mathematical.

Optical data processing.

Database management.

Application software.

Theory of Computation.

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Image Processing and Computer Vision.

Database Management.

Information Systems Applications (incl. Internet).

Local Subjects:

Theory of Computation.

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Image Processing and Computer Vision.

Database Management.

Information Systems Applications (incl. Internet).

Physical Description:

1 online resource (XX, 860 pages).

Edition:

First edition 2004.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-540-25929-9

9783540259299

Access Restriction:

Restricted for use by site license.