000 02511nam a22004575i 4500
001 978-3-319-01640-5
003 DE-He213
005 20170628034036.0
007 cr nn 008mamaa
008 130723s2014 gw | s |||| 0|eng d
020 _a9783319016405
_9978-3-319-01640-5
024 7 _a10.1007/978-3-319-01640-5
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aSzmidt, Eulalia.
_eauthor.
245 1 0 _aDistances and Similarities in Intuitionistic Fuzzy Sets
_h[electronic resource] /
_cby Eulalia Szmidt.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aVIII, 148 p. 35 illus., 17 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v307
505 0 _aIntuitionistic Fuzzy Sets as a Generalization of Fuzzy Sets -- Distances -- Similarity Measures between Intuitionistic Fuzzy Sets.
520 _aThis 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.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319016399
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v307
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-01640-5
912 _aZDB-2-ENG
999 _c18017
_d18017