Intelligent Data Engineering and Automated Learning -- IDEAL 2010
Intelligent Data Engineering and Automated Learning -- IDEAL 2010

Author: Colin Fyfe

Publisher: Springer Science & Business Media

Published: 2010-08-19

Total Pages: 411

ISBN-13: 3642153801

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This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2010, held in Paisley, Scotland, in September 2010. The 47 revised full papers presented were carefully reviewed and selected from many submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.

Intelligent Data Engineering and Automated Learning – IDEAL 2015
Intelligent Data Engineering and Automated Learning – IDEAL 2015

Author: Konrad Jackowski

Publisher: Springer

Published: 2015-10-13

Total Pages: 580

ISBN-13: 3319248340

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This book constitutes the refereed proceedings of the 16th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2015, held in Wroclaw, Poland, in October 2015. The 64 revised full papers presented were carefully reviewed and selected from 127 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modeling, swarm intelligent, multi-objective optimization, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, IDEAL 2015 also featured a number of special sessions on several emerging topics such as computational intelligence for optimization of communication networks, discovering knowledge from data, simulation-driven DES-like modeling and performance evaluation, and intelligent applications in real-world problems.

Intelligent Data Engineering and Automated Learning – IDEAL 2018
Intelligent Data Engineering and Automated Learning – IDEAL 2018

Author: Hujun Yin

Publisher: Springer

Published: 2018-11-08

Total Pages: 890

ISBN-13: 3030034933

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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.

Intelligent Data Engineering and Automated Learning -- IDEAL 2011
Intelligent Data Engineering and Automated Learning -- IDEAL 2011

Author: Hujun Yin

Publisher: Springer Science & Business Media

Published: 2011-08-30

Total Pages: 527

ISBN-13: 3642238777

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This book constitutes the refereed proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2011, held in Norwich, UK, in September 2011. The 59 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.

Intelligent Data Engineering and Automated Learning -- IDEAL 2013
Intelligent Data Engineering and Automated Learning -- IDEAL 2013

Author: Hujun Yin

Publisher: Springer

Published: 2013-10-16

Total Pages: 656

ISBN-13: 3642412785

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This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.

Intelligent Data Engineering and Automated Learning – IDEAL 2021
Intelligent Data Engineering and Automated Learning – IDEAL 2021

Author: Hujun Yin

Publisher: Springer Nature

Published: 2021-11-23

Total Pages: 663

ISBN-13: 3030916081

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This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic. The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.

Intelligent Data Engineering and Automated Learning – IDEAL 2016
Intelligent Data Engineering and Automated Learning – IDEAL 2016

Author: Hujun Yin

Publisher: Springer

Published: 2016-09-12

Total Pages: 664

ISBN-13: 3319462571

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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.

Intelligent Data Engineering and Automated Learning – IDEAL 2023
Intelligent Data Engineering and Automated Learning – IDEAL 2023

Author: Paulo Quaresma

Publisher: Springer Nature

Published: 2023-12-16

Total Pages: 561

ISBN-13: 3031482328

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This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Intelligent Data Engineering and Automated Learning – IDEAL 2023
Intelligent Data Engineering and Automated Learning – IDEAL 2023

Author: Paulo Quaresma

Publisher: Springer

Published: 2023-12-24

Total Pages: 0

ISBN-13: 9783031482311

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This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Intelligent Data Engineering and Automated Learning -- IDEAL 2014
Intelligent Data Engineering and Automated Learning -- IDEAL 2014

Author: Emilio Corchado

Publisher: Springer

Published: 2014-08-13

Total Pages: 524

ISBN-13: 3319108409

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This book constitutes the refereed proceedings of the 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, held in Salamanca, Spain, in September 2014. The 60 revised full papers presented were carefully reviewed and selected from about 120 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition the conference provided a good sample of current topics from methodologies, frameworks, and techniques to applications and case studies. The techniques include computational intelligence, big data analytics, social media techniques, multi-objective optimization, regression, classification, clustering, biological data processing, text processing, and image/video analysis.