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988 _aSpringer_Robotics_2020
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020 _a9783030254322
024 7 _a10.1007/978-3-030-25432-2
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.9 .S63
_b2020 EB
100 1 _aTrujillo-Cabezas, Raúl
_eautor
_9671786
245 1 0 _aIntegrating soft computing into strategic prospective methods :
_btowards an adaptive learning environment supported by futures studies
_cby Raúl Trujillo-Cabezas, José Luis Verdegay
250 _aFirst edition
264 1 _aCham
_bSpringer International Publishing
_c2020
300 _a1 recurso en línea (XXII, 230 páginas)
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aStudies in Fuzziness and Soft Computing
_x1434-9922
_v387
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aIntroduction -- Strategic Prospective: Definitions and Key Concepts -- Fuzzy Optimization and Reasoning Approaches -- Constructing Models -- Modeling and Simulation of the Future -- Experimental Applications: An Overview of New Ways -- Meta-Prospective Toolbox -- A Cloud Environment: A first demo.
520 3 _aThis book discusses how to build optimization tools able to generate better future studies. It aims at showing how these tools can be used to develop an adaptive learning environment that can be used for decision making in the presence of uncertainties. The book starts with existing fuzzy techniques and multicriteria decision making approaches and shows how to combine them in more effective tools to model future events and take therefore better decisions. The first part of the book is dedicated to the theories behind fuzzy optimization and fuzzy cognitive map, while the second part presents new approaches developed by the authors with their practical application to trend impact analysis, scenario planning and strategic formulation. The book is aimed at two groups of readers, interested in linking the future studies with artificial intelligence. The first group includes social scientists seeking for improved methods for strategic prospective. The second group includes computer scientists and engineers seeking for new applications and current developments of Soft Computing methods for forecasting in social science, but not limited to this.
650 7 _2embne
_9166276
_aSoft Computing
650 7 _2embne
_aToma de decisiones
_9141176
700 1 _aVerdegay, José Luis
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
776 0 8 _iPrinted edition:
_z9783030254315
776 0 8 _iPrinted edition:
_z9783030254339
776 0 8 _iPrinted edition:
_z9783030254346
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-25432-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _aSI
_cm
_dz
_feng
_ggw
_h0
_b12/2019
_eel
_zSI