Natural Computing for Unsupervised Learning
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 im…
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Produktdetails
Weitere Autoren: Wong, Ka-Chun (Hrsg.)
- ISBN: 978-3-030-07508-8
- EAN: 9783030075088
- Produktnummer: 33230217
- Verlag: Springer International Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2018
- Seitenangabe: 280 S.
- Masse: H23.5 cm x B15.5 cm x D1.5 cm 429 g
- Auflage: Softcover reprint of the original 1st ed. 2019
- Abbildungen: Paperback
- Gewicht: 429
Über den Autor
Xiangtao Li received the B.Eng. Degree, the M.Eng. and Ph.D. degrees in computer science from Northeast Normal University, Changchun, China in 2009, 2012, 2015, respectively. Now He is an associate professor in the Department of Computer science and information technology, Northeast Normal University. He has published more than 50 research papers. His research interests include intelligent computation, evolutionary data mining, constrained optimization, bioinformatics, computational biology and interdisciplinary research.Ka-Chun Wong received the BEng degree in computer engineering from United College, Chinese University of Hong Kong, in 2008. He received the MPhil degree from the same university in 2010 and the PhD degree from the Department of Computer Science, University of Toronto in 2014. He assumed his duty as an assistant professor at City University of Hong Kong in 2015. His research interests include bioinformatics, computational biology, evolutionary computation, data mining, machine learning, and interdisciplinary research. He is merited as the associate editor of BioData Mining in 2016. In addition, he is on the editorial board of Applied Soft Computing since 2016. He has solely edited 2 books published by Springer and CRC Press, attracting 30 peer-reviewed book chapters around the world.
2 weitere Werke von Xiangtao (Hrsg.) Li:
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