Distances and Similarities in Intuitionistic Fuzzy Sets:
Gespeichert in:
Bibliographische Detailangaben
Beteilige Person: Szmidt, Eulalia (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: 2014
Schriftenreihe:Studies in Fuzziness and Soft Computing 307
Schlagwörter:
Links:https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
https://doi.org/10.1007/978-3-319-01640-5
http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917101&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917101&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
Beschreibung: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
Umfang:1 Online-Ressource (VIII, 148 p.) 35 illus., 17 illus. in color
ISBN:9783319016405
DOI:10.1007/978-3-319-01640-5