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978-3-030-62628-0 |
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20240322103417.0 |
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201218s2021 sz | s |||| 0|eng d |
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|a 9783030626280
|9 978-3-030-62628-0
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|a 10.1007/978-3-030-62628-0
|2 doi
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|a Guidara, Ali.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Policy Decision Modeling with Fuzzy Logic
|h [electronic resource] :
|b Theoretical and Computational Aspects /
|c by Ali Guidara.
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| 250 |
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|a 1st ed. 2021.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2021.
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| 300 |
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|a XII, 134 p. 30 illus., 25 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Studies in Fuzziness and Soft Computing,
|x 1860-0808 ;
|v 405
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| 505 |
0 |
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|a Chapter 1. Decision Process and Analytical Frameworks – Levels of Analysis and Paradigmatic Evolution -- Chapter 2. Complex Systems and Public Policy -- Chapter 3. Multiple Streams theory -- Chapter 4. Artificial Intelligence and Fuzzy Logic -- Chapter 5. PODESIM – Policy Decision Emergence Simulation Model 93 -- Chapter 6. Analysis of Results -- Chapter 7. Innovation and Contributions. .
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| 520 |
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|a This book introduces the concept of policy decision emergence and its dynamics at the sub systemic level of the decision process. This level constitutes the breeding ground of the emergence of policy decisions but remains unexplored due to the absence of adequate tools. It is a nonlinear complex system made of several entities that interact dynamically. The behavior of such a system cannot be understood with linear and deterministic methods. The book presents an innovative multidisciplinary approach that results in the development of a Policy Decision Emergence Simulation Model (PODESIM). This computational model is a multi-level fuzzy inference system that allows the identification of the decision emergence levers. This development represents a major advancement in the field of public policy decision studies. It paves the way for decision emergence modeling and simulation by bridging complex systems theory, multiple streams theory, and fuzzy logic theory.
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| 650 |
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|a Computational intelligence.
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| 650 |
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|a Political planning.
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| 650 |
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|a Control engineering.
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| 650 |
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|a Computational complexity.
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| 650 |
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4 |
|a Computational Intelligence.
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| 650 |
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|a Public Policy.
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| 650 |
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|a Control and Systems Theory.
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| 650 |
2 |
4 |
|a Computational Complexity.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9783030626273
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| 776 |
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|i Printed edition:
|z 9783030626297
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| 776 |
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8 |
|i Printed edition:
|z 9783030626303
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| 830 |
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|a Studies in Fuzziness and Soft Computing,
|x 1860-0808 ;
|v 405
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-62628-0
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| 912 |
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|a ZDB-2-INR
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| 912 |
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|a ZDB-2-SXIT
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| 950 |
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|a Intelligent Technologies and Robotics (SpringerNature-42732)
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| 950 |
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|a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)
|