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|a 9783319082486
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|a 10.1007/978-3-319-08248-6
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|a (DE-He213)978-3-319-08248-6
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| 100 |
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|a C. Casey, Peter.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 245 |
1 |
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|a Fuzzy Social Choice Models
|h [electronic resource] :
|b Explaining the Government Formation Process /
|c by Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman, Terry D. Clark.
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| 250 |
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|a 1st ed. 2014.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2014.
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| 300 |
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|a XIII, 183 p. 29 illus.
|b online resource.
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| 347 |
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|b PDF
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| 490 |
1 |
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 318
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| 490 |
1 |
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|a Springer eBook Collection
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| 505 |
0 |
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|a A 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.
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| 520 |
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|a This 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. .
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| 590 |
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|a Loaded electronically.
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| 590 |
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|a Electronic access restricted to members of the Holy Cross Community.
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| 650 |
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|a Computational intelligence.
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| 650 |
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|a Political science.
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| 650 |
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|a Mathematics.
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| 650 |
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|a Social sciences.
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| 690 |
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|a Electronic resources (E-books)
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| 700 |
1 |
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|a B. Gibilisco, Michael.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 700 |
1 |
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|a A. Goodman, Carly.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 700 |
1 |
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|a Pook, Kelly Nelson.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 700 |
1 |
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|a N. Mordeson, John.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 700 |
1 |
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|a J. Wierman, Mark.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 700 |
1 |
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|a D. Clark, Terry.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 710 |
2 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 830 |
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|a Studies in Fuzziness and Soft Computing,
|x 1434-9922 ;
|v 318
|
| 830 |
|
0 |
|a Springer eBook Collection.
|
| 856 |
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