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001 978-1-4614-6666-6
003 DE-He213
005 20200421112046.0
007 cr nn 008mamaa
008 130625s2013 xxu| s |||| 0|eng d
020 _a9781461466666
_9978-1-4614-6666-6
024 7 _a10.1007/978-1-4614-6666-6
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aAdvances in Type-2 Fuzzy Sets and Systems
_h[electronic resource] :
_bTheory and Applications /
_cedited by Alireza Sadeghian, Jerry M. Mendel, Hooman Tahayori.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aX, 262 p. 103 illus., 41 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 ;
_v301
505 0 _aPart 1 - Theoretical Foundations -- Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences -- Continuous Karnik-Mendel Algorithms and Their Generalizations -- Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty -- Interval Type-2 Fuzzy Markov Chains -- zSlices Based General Type-2 Fuzzy Sets and Systems -- Geometric Type-2 Fuzzy Sets -- Type-2 Fuzzy Sets and Bichains -- Type-2 Fuzzy Sets and Conceptual Spaces -- Part B- Type-2 Fuzzy Set Membership Function Generation -- Modeling Complex Concepts with Type-2 Fuzzy Sets: The Case of User Satisfaction of Online Services.-  Construction of Interval type-2 fuzzy sets from fuzzy sets. Methods and applications -- Interval type-2 fuzzy membership function generation methods for representing sample data -- Part C - Applications -- ype-2 Fuzzy Logic in Image Analysis and Pattern Recognition -- Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic -- A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R -- Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application.
520 _aThis book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet.  The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aSadeghian, Alireza.
_eeditor.
700 1 _aMendel, Jerry M.
_eeditor.
700 1 _aTahayori, Hooman.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461466659
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v301
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-6666-6
912 _aZDB-2-ENG
942 _cEBK
999 _c56907
_d56907