Distances and Similarities in Intuitionistic Fuzzy Sets (Record no. 57758)
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fixed length control field | 02617nam a22005055i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-01640-5 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421112227.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 130723s2014 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319016405 |
-- | 978-3-319-01640-5 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.3 |
100 1# - AUTHOR NAME | |
Author | Szmidt, Eulalia. |
245 10 - TITLE STATEMENT | |
Title | Distances and Similarities in Intuitionistic Fuzzy Sets |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | VIII, 148 p. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Fuzziness and Soft Computing, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Intuitionistic Fuzzy Sets as a Generalization of Fuzzy Sets -- Distances -- Similarity Measures between Intuitionistic Fuzzy Sets. |
520 ## - SUMMARY, ETC. | |
Summary, etc | This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers with a comprehensive set of theoretical concepts and practical tools for both defining and determining similarity between intuitionistic fuzzy sets. It describes an automatic algorithm for deriving intuitionistic fuzzy sets from data, which can aid in the analysis of information in large databases. The book also discusses other important applications, e.g. the use of similarity measures to evaluate the extent of agreement between experts in the context of decision making. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-01640-5 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
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-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2014. |
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-- | computer |
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-- | rdamedia |
338 ## - | |
-- | online resource |
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347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Operations research. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Management science. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Operations Research, Management Science. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence (incl. Robotics). |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 1434-9922 ; |
912 ## - | |
-- | ZDB-2-ENG |
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