Self-Learning and Adaptive Algorithms for Business Applications - A Guide to Adaptive Neuro-Fuzzy Systems for Fuzzy Clustering Under Uncertainty Conditions (Paperback)

In today's data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications. In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning.

General

Imprint:	Emerald Publishing Limited
Country of origin:	United Kingdom
Series:	Emerald Points
Release date:	June 2019
First published:	2019
Authors:	Zhengbing Hu • Yevgeniy V. Bodyanskiy • Oleksii Tyshchenko
Dimensions:	198 x 129 x 22mm (L x W x T)
Format:	Paperback
Pages:	120
ISBN-13:	978-1-83867-174-7
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Business & Economics > Business & management > Management of specific areas > Research & development management Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Promotions
LSN:	1-83867-174-9
Barcode:	9781838671747

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