Intelligent data engineering and automated learning -- IDEAL 2018 :
General Material Designation
[Book]
Other Title Information
19th International Conference, Madrid, Spain, November 21-23, 2018, Proceedings.
First Statement of Responsibility
Hujun Yin, David Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros (eds.).
Volume Designation
Part I /
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Cham, Switzerland :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xxvi, 865 pages) :
Other Physical Details
illustrations (some color)
SERIES
Series Title
Lecture notes in computer science ;
Series Title
LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
Volume Designation
11314
GENERAL NOTES
Text of Note
Includes author index.
Text of Note
International conference proceedings.
CONTENTS NOTE
Text of Note
Intelligent data analysis -- data mining and their associated learning systems and paradigms -- big data challenges -- machine learning, data mining, information retrieval and management -- bio- and neuro-informatics -- bio-inspired models including neural networks, evolutionary computation and swarm intelligence -- agents and hybrid intelligent systems, and real-world applications of intelligent techniques -- evolutionary algorithms -- deep learning neural networks -- probabilistic modeling -- particle swarm intelligence -- big data analytics and applications in image recognition -- regression, classification, clustering, medical and biological modelling and prediction -- text processing and social media analysis.
0
SUMMARY OR ABSTRACT
Text of Note
This two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.