{"product_id":"natural-computing-for-unsupervised-learning-hardcover","title":"Natural Computing for Unsupervised Learning - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eXiangtao Li\u003c\/b\u003e (Editor), \u003cb\u003eKa-Chun Wong\u003c\/b\u003e (Editor)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eIncludes advances on unsupervised learning using natural computing techniques\u003c\/p\u003e \u003cp\u003eReports on topics in emerging areas such as evolutionary multi-objective unsupervised learning\u003c\/p\u003e \u003cp\u003eFeatures natural computing techniques such as evolutionary multi-objective algorithms, and many-objective swarm intelligence algorithms\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis 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. \u003c\/p\u003e\u003cp\u003eIncludes advances on unsupervised learning using natural computing techniques\u003c\/p\u003e\u003cp\u003eReports on topics in emerging areas such as evolutionary multi-objective unsupervised learning\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eFeatures natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003eXiangtao 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.\u003cbr\u003eKa-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.\u003cbr\u003e\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 273\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.69 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 12, 2018\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212908151033,"sku":"9783319985657","price":178.18,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/Yy9zK0VWME8vVXFQYW5xNnY5cWx5dz09.webp?v=1768098940","url":"https:\/\/bookscloud.io\/products\/natural-computing-for-unsupervised-learning-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}