Big data : conceptual analysis and applications
- Responsibility
- Michael Z. Zgurovsky, Yuriy P. Zaychenko.
- Publication
- Cham, Switzerland : Springer, [2020]
- Physical description
- 1 online resource (xxiii, 277 pages) : illustrations (some color)
- Series
- Studies in big data ; v. 58. 2197-6503
Online
Available online
More options
Description
Creators/Contributors
- Author/Creator
- Zhurovsʹkyĭ, M. Z. (Mykhaĭlo Zakharovych) author.
- Contributor
- Zaychenko, Yuriy P., author.
Contents/Summary
- Contents
-
- Cluster Analysis in Big Data Mining.- Deep Neural Networks and Hybrid GMDH
- Neuro-fuzzy Networks in Big Data Analysis.- Pattern Recognition in Big Data Analysis.- Intellectual analysis of systemic world conflicts and global forecast for the 21st century.
- Summary
- The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.
Subjects
- Subjects
- Big data.
Bibliographic information
- Publication date
- 2020
- Series
- Studies in big data, 2197-6503 ; volume 58
- ISBN
- 9783030142988 (electronic bk.)
- 3030142981 (electronic bk.)
- 9783030142971 (print)
- DOI
- 10.1007/978-3-030-14298-8
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