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.

Format:

Book

Contributor:

Yin, Hujun., Editor.

Gao, Yang, Editor.

Li, Bin, Editor.

Zhang, Daoqiang, Editor.

Yang, Ming, Editor.

Li, Yun, Editor.

Klawonn, F., Editor.

Tallón-Ballesteros, Antonio J., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 9937

Information Systems and Applications, incl. Internet/Web, and HCI ; 9937

Language:

English

Subjects (All):

Data mining.

Pattern recognition systems.

Artificial intelligence.

Algorithms.

Information storage and retrieval systems.

Computer science.

Data Mining and Knowledge Discovery.

Automated Pattern Recognition.

Artificial Intelligence.

Information Storage and Retrieval.

Theory of Computation.

Local Subjects:

Data Mining and Knowledge Discovery.

Automated Pattern Recognition.

Artificial Intelligence.

Algorithms.

Information Storage and Retrieval.

Theory of Computation.

Physical Description:

1 online resource (XVI, 647 pages) : 209 illustrations

Edition:

1st ed. 2016.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

System Details:

text file PDF

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 analysis. .

Contents:

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 analysis.

Other Format:

Printed edition:

ISBN:

978-3-319-46257-8

9783319462578

Access Restriction:

Restricted for use by site license.