000			03966nam a22004215i 4500
999			_c85235 _d85235 _x1
001			85235
003			ES-MaUEC
005			20240111050121.0
007			cr nn 008mamaa
008			151208s2016 gw | s |||| 0|eng d
020			_a9783319267180
040			_aES-MaUEC
050		4	_aQA9.64 _bB579 2016
082	0	4	_a006.3
100	1		_aBiswas, Ranjit _998037 _0Local _c(Computer scientist)
245	1	0	_aIs Fuzzy Theory an Appropriate Tool for Large Size Problems? _cby Ranjit Biswas
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (VIII, 64 p.) _b17 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	1		_aSpringerBriefs in Applied Sciences and Technology _x2191-530X
505	0		_aTwo Hidden Facts about Fuzzy Set Theory (and, about any Soft Computing Set Theory) -- Cognitive Intuitionistic Fuzzy System (CIFS) -- Is Fuzzy Theory? an Appropriate Tool for Large Size Problems? -- Ordering (or Ranking) of Elements in an IFS on the basis of Their Amount of Belongingness -- An Application Domain to Understand the Potential of Intuitionistic Fuzzy Theory over Fuzzy Theory -- An Example of Application Domain to Understand the Potential of Fuzzy Theory over Intuitionistic Fuzzy Theory in Some Cases -- Conclusion -- Future Research Directions.
520			_aThe work in this book is based on philosophical as well as logical views on the subject of decoding the progress of decision making process in the cognition system of a decision maker (be it a human or an animal or a bird or any living thing which has a brain) while evaluating the membership value (x) in a fuzzy set or in an intuitionistic fuzzy set or in any such soft computing set model or in a crisp set. A new theory is introduced called by zTheory of CIFSy. The following two hypothesis are hidden facts in fuzzy computing or in any soft computing process :- Fact-1: A decision maker (intelligent agent) can never use or apply fuzzy theory or any soft-computing set theory without intuitionistic fuzzy system. Fact-2 : The Fact-1 does not necessarily require that a fuzzy decision maker (or a crisp ordinary decision maker or a decision maker with any other soft theory models or a decision maker like animal/bird which has brain, etc.) must be aware or knowledgeable about IFS Theory! The zTheory of CIFSy is developed with a careful analysis unearthing the correctness of these two facts. Two examples of decision making problems with complete solutions are presented out of which one example will show the dominance of the application potential of intuitionistic fuzzy set theory over fuzzy set theory, and the other will show the converse i.e. the dominance of the application potential of fuzzy set theory over intuitionistic fuzzy set theory in some cases. The zTheory of CIFSy may be viewed to belong to the subjects : Theory of Intuitionistic Fuzzy Sets, Soft Computing, Artificial Intelligence, etc.
650		7	_aInteligencia artificial _0comprobar BNE19900997218 _2embne _9413115
650	0	7	_9152594 _aLógica difusa _0LocalX _2embne
650	0	7	_aIngeniería _vCongresos y asambleas _0LocalX _2embne _9670301
710	2		_aSpringerLink (Online service) _0Local _9106996
830		0	_aSpringerBriefs in Applied Sciences and Technology _x2191-530X _9134085
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-26718-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319267180
907			_a.b12945134 _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aQA9.64 B579 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11589073 _z06-04-17
988	0	0	_aEBOOK, EBSPRINGER
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0