Intelligent Data Engineering and Automated Learning – IDEAL 2017

Intelligent Data Engineering and Automated Learning – IDEAL 2017 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3319689355
Category : Computers
Languages : en
Pages : 626

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Book Description
This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017. The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample 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, 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 2017

Intelligent Data Engineering and Automated Learning – IDEAL 2017 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3319689355
Category : Computers
Languages : en
Pages : 626

Get Book Here

Book Description
This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017. The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample 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, 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 2016

Intelligent Data Engineering and Automated Learning – IDEAL 2016 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3319462571
Category : Computers
Languages : en
Pages : 664

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Book Description
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 2022

Intelligent Data Engineering and Automated Learning – IDEAL 2022 PDF Author: Hujun Yin
Publisher: Springer Nature
ISBN: 3031217535
Category : Computers
Languages : en
Pages : 564

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Book Description
This book constitutes the refereed proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022, which took place in Manchester, UK, during November 24-26, 2022. The 52 full papers included in this book were carefully reviewed and selected from 79 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 2020

Intelligent Data Engineering and Automated Learning – IDEAL 2020 PDF Author: Cesar Analide
Publisher: Springer Nature
ISBN: 3030623629
Category : Computers
Languages : en
Pages : 424

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Book Description
This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.

Intelligent Data Engineering and Automated Learning – IDEAL 2023

Intelligent Data Engineering and Automated Learning – IDEAL 2023 PDF Author: Paulo Quaresma
Publisher: Springer Nature
ISBN: 3031482328
Category : Computers
Languages : en
Pages : 561

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Book Description
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 2018

Intelligent Data Engineering and Automated Learning – IDEAL 2018 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3030034933
Category : Computers
Languages : en
Pages : 890

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Book Description
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 2013

Intelligent Data Engineering and Automated Learning -- IDEAL 2013 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3642412785
Category : Computers
Languages : en
Pages : 656

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Book Description
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

Intelligent Data Engineering and Automated Learning PDF Author:
Publisher:
ISBN:
Category : Data mining
Languages : en
Pages : 602

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Book Description


Intelligent Data Engineering and Automated Learning -- IDEAL 2012

Intelligent Data Engineering and Automated Learning -- IDEAL 2012 PDF Author: Hujun Yin
Publisher: Springer
ISBN: 3642326390
Category : Computers
Languages : en
Pages : 882

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Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.

Data Clustering

Data Clustering PDF Author:
Publisher: BoD – Books on Demand
ISBN: 183969887X
Category : Computers
Languages : en
Pages : 128

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Book Description
In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data.