LEADER 03728nam  22006255  450 
001 9910136003603321
005 20220415193816.0
010   $a3-319-45928-7
024 7 $a10.1007/978-3-319-45928-8
035   $a(CKB)3710000000909138
035   $a(DE-He213)978-3-319-45928-8
035   $a(MiAaPQ)EBC4721355
035   $a(PPN)196326281
035   $a(EXLCZ)993710000000909138
100   $a20161020d2016      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aGeneralizations of fuzzy information measures /$fby Anshu Ohlan, Ramphul Ohlan
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (IX, 146 p. 7 illus.)
311   $a3-319-45927-9 
320   $aIncludes bibliographical references at the end of each chapters and index.
327   $aFundamentals of Fuzzy Information Measures -- Parametric Generalized R?Norm Fuzzy Information and Divergence Measures -- Parametric Generalized R?Norm Fuzzy Information and Divergence Measures -- Parametric Generalized Exponential Fuzzy Divergence Measure and Strategic Decision Making -- Sequence and Application of Inequalities Among Fuzzy Mean Difference Divergence Measures in Pattern Recognition -- Applications of Generalized Fuzzy Divergence Measure in Multi-criteria Decision Making and Pattern Recognition -- Generalized Hellinger?s Fuzzy Divergence Measure and Its Applications -- Intuitionistic Fuzzy Exponential Divergence and Multi-Attribute Decision Making.
330   $aThis book develops applications of novel generalizations of fuzzy information measures in the field of pattern recognition, medical diagnosis, multi-criteria and multi-attribute decision making and suitability in linguistic variables. The focus of this presentation lies on introducing consistently strong and efficient generalizations of information and information-theoretic divergence measures in fuzzy and intuitionistic fuzzy environment covering different practical examples. The target audience comprises primarily researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
606   $aPattern recognition
606   $aComputer mathematics
606   $aComputational complexity
606   $aBiometrics (Biology)
606   $aApplied linguistics
606   $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
606   $aComputational Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/M14026
606   $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022
606   $aBiometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22040
606   $aApplied Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N13000
615  0$aPattern recognition.
615  0$aComputer mathematics.
615  0$aComputational complexity.
615  0$aBiometrics (Biology).
615  0$aApplied linguistics.
615 14$aPattern Recognition.
615 24$aComputational Science and Engineering.
615 24$aComplexity.
615 24$aBiometrics.
615 24$aApplied Linguistics.
676   $a006.4
700   $aOhlan$b Anshu$4aut$4http://id.loc.gov/vocabulary/relators/aut$0922402
702   $aOhlan$b Ramphul$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910136003603321
996   $aGeneralizations of Fuzzy Information Measures$92069858
997   $aUNINA