Overview
- This book is about going beyond traditional probabilistic data processing techniques, to pursue interval, fuzzy, etc. methods – how to do it, and what the applications of the resulting non-traditional approaches are
- Dedicated to Vladik Kreinovich on the occasion of his 65th birthday
- Includes papers on constructive mathematics, fuzzy techniques, interval computations, uncertainty in general, and neural networks
Part of the book series: Studies in Computational Intelligence (SCI, volume 835)
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About this book
In this book, leading specialists on interval, fuzzy, probabilistic uncertainty and their combination describe state-of-the-art developments in their research areas. Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitablefor graduate students.
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Keywords
Table of contents (36 chapters)
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Constructive Mathematics
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Fuzzy Techniques
Editors and Affiliations
Bibliographic Information
Book Title: Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications
Editors: Olga Kosheleva, Sergey P. Shary, Gang Xiang, Roman Zapatrin
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-31041-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-31040-0Published: 29 February 2020
Softcover ISBN: 978-3-030-31043-1Published: 26 August 2021
eBook ISBN: 978-3-030-31041-7Published: 28 February 2020
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XI, 649
Number of Illustrations: 71 b/w illustrations, 71 illustrations in colour
Topics: Data Engineering, Computational Intelligence, Artificial Intelligence