TY  - BOOK
AU  - Hu,Zhengbing
AU  - Bodyanskiy,Yevgeniy V.
AU  - Tyshchenko,Oleksii
TI  - Self-learning and adaptive algorithms for business applications: a guide to adaptive neuro-fuzzy systems for fuzzy clustering under uncertainty conditions 
T2  - Emerald points
SN  - 9781838671716 (e-book)
AV  - HF5548.2 .H89 2019
U1  - 658.054 23
PY  - 2019///
CY  - Bingley, U.K.
PB  - Emerald Publishing Limited
KW  - Business
KW  - Data processing
KW  - Electronic data processing
KW  - Fuzzy systems
KW  - Business & Economics
KW  - Research & Development
KW  - bisacsh
KW  - Neural networks & fuzzy systems
KW  - bicssc
N1  - Includes bibliographical references; Prelims -- Introduction -- Review of the problem area -- Adaptive methods of fuzzy clustering -- Kohonen maps and their ensembles for fuzzy clustering tasks -- Simulation results and solutions for practical tasks -- Conclusion -- References
N2  - 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.
UR  - https://www.emerald.com/insight/publication/doi/10.1108/9781838671716
ER  -