Intelligent Data Engineering and Automated Learning – IDEAL 2016 : 17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings / edited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tallón-Ballesteros

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink Bücher | Springer eBook Collection Computer Science | Lecture notes in computer science ; 9937Publisher: Cham : Springer, 2016Description: Online-Ressource (XVI, 647 p. 209 illus, online resource)ISBN:

9783319462578

Subject(s): Additional physical formats: 9783319462561 | Erscheint auch als: 978-3-319-46256-1 Druck-Ausgabe | Printed edition: 9783319462561 LOC classification:

QA76.9.D343

DOI: DOI: 10.1007/978-3-319-46257-8Online resources:

Summary: This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysisSummary: Research outcomes in data engineering and automated learning -- Methodologies, frameworks, and techniques -- Applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis -- Applications in regression, classification, clustering, medical and biological modeling and predication -- Text processing and image analysisPPN: PPN: 1658921178Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB | ZDB-2-SEB

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