Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings /

The IDEAL conference has become a unique, established and broad interdisciplinary forum for experts, researchers and practitioners in many fields to interact with each other and with leading academics and industries in the areas of machine learning, information processing, data mining, knowledge man...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Fyfe, Colin (Επιμελητής έκδοσης), Tino, Peter (Επιμελητής έκδοσης), Charles, Darryl (Επιμελητής έκδοσης), Garcia-Osorio, Cesar (Επιμελητής έκδοσης), Yin, Hujun (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010.
Σειρά:Lecture Notes in Computer Science, 6283
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη:The IDEAL conference has become a unique, established and broad interdisciplinary forum for experts, researchers and practitioners in many fields to interact with each other and with leading academics and industries in the areas of machine learning, information processing, data mining, knowledge management, bio-informatics, neu- informatics, bio-inspired models, agents and distributed systems, and hybrid systems. This volume contains the papers presented at the 11th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2010), which was held September 1–3, 2010 in the University of the West of Scotland, on its Paisley campus, 15 kilometres from the city of Glasgow, Scotland. All submissions were strictly pe- reviewed by the Programme Committee and only the papers judged with sufficient quality and novelty were accepted and included in the proceedings. The IDEAL conferences continue to evolve and this year’s conference was no exc- tion. The conference papers cover a wide variety of topics which can be classified by technique, aim or application. The techniques include evolutionary algorithms, artificial neural networks, association rules, probabilistic modelling, agent modelling, particle swarm optimization and kernel methods. The aims include regression, classification, clustering and generic data mining. The applications include biological information processing, text processing, physical systems control, video analysis and time series analysis.
Φυσική περιγραφή:XVI, 398 p. 134 illus. online resource.
ISBN:9783642153815
ISSN:0302-9743 ;