Kniha Fuzzy Systems and Knowledge Discovery Lipo Wang

Fuzzy Systems and Knowledge Discovery

Second International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I

Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: 50 % šance
Prohledáme celý svět
3 058
The two volume set LNAI 3613 and LNAI 3614 constitutes the refereed§proceedings of the Second Intern...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2005
Stránek
1334
EAN
9783540283126
ISBN
3540283129
Enbook ID
01561000
Hmotnost
1503
Rozměry
155 x 235 x 50

Kompletní popis

The two volume set LNAI 3613 and LNAI 3614 constitutes the refereed§proceedings of the Second International Conference on Fuzzy Systems and§Knowledge Discovery, FSKD 2005, held in Changsha, China, in August 2005 as a joint event in federation with the First International Conference on Natural Computation ICNC 2005 (LNCS volumes 3610, 3611, and 3612).§The program committee selected 206 carefully revised full papers and 127 short papers for presentation in two volumes from 1249 submissions. The first volume includes all the contributions related to fuzzy theory and models, uncertainty management and probabilistic methods in data mining, approximate reasoning, axiomatic foundation, fuzzy classifiers, fuzzy clustering, fuzzy database mining and information retrieval, information fusion, neuro-fuzzy systems, fuzzy control, fuzzy hardware, knowledge visualization and exploration, sequential data analysis, parallel and distributed data mining, and rough sets. The second volume deals with dimensionality reduction, pattern recognition and trend analysis, other topics in FSKD methods, mining of spatial, textual, image and time-series data, fuzzy systems in bioinformatics and bio-medical engineering, in expert system and informatics, and in pattern recognition and diagostics; knowledge discovery in bioinformatics, bio-medical engineering, and in expert system and informatics; active information gathering on the web, and neural and fuzzy computation in cognitive computer vision.

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