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Books on the topic 'Fuzzy selection'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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1

Ramaswamy, Srichander. Portfolio selection using fuzzy decision theory. Bank for International Settlements, Monetary and Economic Dept., 1998.

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2

Jensen, Richard. Computational intelligence and feature selection: Rough and fuzzy approaches. Wiley, 2008.

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3

Kitainik, Leonid. Fuzzy decision procedures with binary relations: Towards a unified theory. Kluwer Academic Publishers, 1993.

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4

United States. National Aeronautics and Space Administration., ed. Fuzzy sets, rough sets, and modeling evidence: Theory and application : a Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection. Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1992.

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5

Korvin, Andre De. Fuzzy sets, rough sets, and modeling evidence: Theory and application : a Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection. Research Institute for Computing and Information Systems, University of Houston-Clear Lake, 1992.

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6

Cao, Bing-Yuan. Optimal Models and Methods with Fuzzy Quantities. Springer-Verlag Berlin Heidelberg, 2010.

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7

Babanli, Mustafa B. Fuzzy Logic-Based Material Selection and Synthesis. World Scientific Publishing Co Pte Ltd, 2019.

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8

Jensen, Richard, and Qiang Shen. Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches. Wiley & Sons, Incorporated, John, 2008.

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9

Jensen, Richard, and Qiang Shen. Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches. Wiley & Sons, Incorporated, John, 2008.

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10

Kitainik, Leonid. Fuzzy Decision Procedures with Binary Relations: Towards a Unified Theory. Springer London, Limited, 2012.

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11

Kitainik, Leonid. Fuzzy Decision Procedures with Binary Relations: Towards A Unified Theory. Springer, 2012.

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12

Hudec, Miroslav. Fuzziness in Information Systems: How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization. Springer, 2016.

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13

Hudec, Miroslav. Fuzziness in Information Systems: How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization. Springer London, Limited, 2016.

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14

Hudec, Miroslav. Fuzziness in Information Systems: How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization. Springer, 2018.

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15

Cao, Bing-Yuan. Optimal Models and Methods with Fuzzy Quantities. Springer Berlin / Heidelberg, 2012.

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16

Cao, Bing-Yuan. Optimal Models and Methods with Fuzzy Quantities. Springer, 2010.

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17

Demirli, Kudret. A unified and extended framework for operator selection in generalized modus ponens type fuzzy reasoning. 1995.

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18

Ran, Hirschl. 6 Case Selection and Research Design in Comparative Constitutional Studies. Oxford University Press, 2014. http://dx.doi.org/10.1093/acprof:oso/9780198714514.003.0007.

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Abstract:
Comparative constitutional law’s methodological matrix is fuzzy and amorphous. A close look at social science methods suggests a toolkit of considerations to be addressed in conducting comparative constitutional inquiry, thus supporting various types of comparative constitutional studies. The meanings, purposes, and modes of comparative inquiry in contemporary comparative constitutional studies are identified; some basic principles of case selection and research design employed in inference-oriented small-N studies are presented; and the emerging world of multivariate, large-N studies is explo
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19

Mertens, Marvin. Evaluation of the Fuzzy Attractiveness of Market Entry (Fame) Model for Market Selection Decisions and the Related Modelling Process. GRIN Verlag GmbH, 2015.

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20

Bhatt, Rajen. Fuzzy-Rough Approaches for Pattern Classification: Hybrid Measures, Mathematical Analysis, Feature Selection Algorithms, Decision Tree Algorithms, Neural Learning, and Applications. Independently Published, 2017.

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21

Pepper, Jen. Shari Urquhart: Selections from the Fuzzy Museum and Other Warm Worlds. Indy Pub, 2021.

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