000			03776nam a22006015i 4500
001			978-3-319-08248-6
003			DE-He213
005			20160615105810.0
007			cr nn 008mamaa
008			140620s2014 gw | s |||| 0|eng d
020			_a9783319082486 _9978-3-319-08248-6
024	7		_a10.1007/978-3-319-08248-6 _2doi
049			_aAlfaisal Main Library
050		4	_aQ342
072		7	_aUYQ _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
100	1		_aC. Casey, Peter. _eauthor.
245	1	0	_aFuzzy Social Choice Models _h[electronic resource] : _bExplaining the Government Formation Process / _cby Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman, Terry D. Clark.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014.
300			_aXIII, 183 p. 29 illus. _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 ; _v318
505	0		_aA Fuzzy Public Choice Model -- Fuzzy Preferences: Extraction from Data and Their Use in Public Choice Models -- Fuzzy Single-Dimensional Public Choice Models -- Fuzzy Single-Dimensional Models -- Multi-Dimensional Models -- Government Formation Process -- The Beginnings of a Weighted Model & New Frontiers.
520			_aThis book explores the extent to which fuzzy set logic can overcome some of the shortcomings of public choice theory, particularly its inability to provide adequate predictive power in empirical studies. Especially in the case of social preferences, public choice theory has failed to produce the set of alternatives from which collective choices are made.  The book presents empirical findings achieved by the authors in their efforts to predict the outcome of government formation processes in European parliamentary and semi-presidential systems.  Using data from the Comparative Manifesto Project (CMP), the authors propose a new approach that reinterprets error in the coding of CMP data as ambiguity in the actual political positions of parties on the policy dimensions being coded. The range of this error establishes parties’ fuzzy preferences. The set of possible outcomes in the process of government formation is then calculated on the basis of both the fuzzy Pareto set and the fuzzy maximal set, and the predictions are compared with those made by two conventional approaches as well as with the government that was actually formed. The comparison shows that, in most cases, the fuzzy approaches outperform their conventional counterparts. .
650		0	_aEngineering.
650		0	_aPolitical science.
650		0	_aMathematics.
650		0	_aSocial sciences.
650		0	_aComputational intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aPolitical Science.
650	2	4	_aMathematics in the Humanities and Social Sciences.
655		7	_aElectronic books. _2local
700	1		_aB. Gibilisco, Michael. _eauthor.
700	1		_aA. Goodman, Carly. _eauthor.
700	1		_aPook, Kelly Nelson. _eauthor.
700	1		_aN. Mordeson, John. _eauthor.
700	1		_aJ. Wierman, Mark. _eauthor.
700	1		_aD. Clark, Terry. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319082479
830		0	_aStudies in Fuzziness and Soft Computing, _x1434-9922 ; _v318
856	4	0	_uhttp://ezproxy.alfaisal.edu/login?url=http://dx.doi.org/10.1007/978-3-319-08248-6
912			_aZDB-2-ENG
942			_2lcc _cEBOOKS
999			_c271837 _d271837