Authors:
- Offers a concise introduction to interval-valued fuzzy methods
- Describes novel classification algorithms
- Reports on new types of interval-valued aggregations
Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 378)
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Table of contents (8 chapters)
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Front Matter
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Foundations
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Front Matter
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Applications
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Front Matter
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Back Matter
About this book
This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information.
Authors and Affiliations
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Faculty of Mathematics and Natural Sciences, University of Rzeszów, Rzeszów, Poland
Urszula Bentkowska
Bibliographic Information
Book Title: Interval-Valued Methods in Classifications and Decisions
Authors: Urszula Bentkowska
Series Title: Studies in Fuzziness and Soft Computing
DOI: https://doi.org/10.1007/978-3-030-12927-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-12926-2Published: 20 February 2019
Softcover ISBN: 978-3-030-12929-3Published: 14 August 2020
eBook ISBN: 978-3-030-12927-9Published: 08 February 2019
Series ISSN: 1434-9922
Series E-ISSN: 1860-0808
Edition Number: 1
Number of Pages: XV, 163
Number of Illustrations: 7 b/w illustrations, 5 illustrations in colour
Topics: Computational Intelligence, Computational Biology/Bioinformatics, Microarrays, Simulation and Modeling