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Natural Computing for Unsupervised Learning

Autor: Xiangtao Li, Ka-Chun Wong

Jazyk:

Vazba: Pevná

Vydavatel: Springer International Publishing AG

Dostupnost: Skladem u dodavatele

Odesíláme za 10-13 dnů

2 286 Kč

This book highlights recent research advances in unsupervised learning using natural computing techn...

Informace o knize

Autor

Xiangtao Li, Ka-Chun Wong

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2018

Stránek

273

EAN

9783319985657

ISBN

3319985655

Enbook ID

19777031

Vydavatel

Springer International Publishing AG

Hmotnost

588

Rozměry

155 x 235 x 21

Kompletní popis

This book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, artificial life, quantum computing, DNA computing, and others. The book also includes information on the use of natural computing techniques for unsupervised learning tasks. It features several trending topics, such as big data scalability, wireless network analysis, engineering optimization, social media, and complex network analytics. It shows how these applications have triggered a number of new natural computing techniques to improve the performance of unsupervised learning methods. With this book, the readers can easily capture new advances in this area with systematic understanding of the scope in depth. Readers can rapidly explore new methods and new applications at the junction between natural computing and unsupervised learning. Includes advances on unsupervised learning using natural computing techniques Reports on topics in emerging areas such as evolutionary multi-objective unsupervised learning Features natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms

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