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020 _a9783030956912
024 7 _a10.1007/978-3-030-95691-2
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA274.2-.28
_b2022 EB
050 4 _aHD61
_b2022 EB
100 1 _aArtikis, Panagiotis
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9683362
245 1 0 _aRandom Contractions in Global Risk Governance
_cby Panagiotis T. Artikis, Constantinos T. Artikis
250 _aFirst edition 2022
264 1 _aCham
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (X, 285 páginas)
_b1 ilustración
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aarchivo de texto
_bPDF
490 0 _aLearning and Analytics in Intelligent Systems
_x2662-3455
_v27
505 0 _aChapter 1: Stochastic Concepts in Global Risk Governance Operations -- Chapter 2: Formulation of a Stochastic Model -- Chapter 3: Random Contraction Representation for a Stochastic Model -- Chapter 4: Interpretation of a Stochastic Model in Global Risk Governance.
520 _aThis book contributes to the area of ongoing global risks and the area of forthcoming global risks, particularly necessary for the implementation of very important interdisciplinary research activities. Global risks are defined in this study as having a global geographical scope, an inter-industrial presence, and exceptionally critical stages of economic and social participation that necessitate a major multi-stakeholder input. In addition, global risks demand an extremely extensive priority in decision-making allowance. The theoretical and practical results of this work are strongly connected to several quite useful factors. The present work mainly concentrates on the contribution of probability theory in the advancement of the practical applicability of global risk governance. More precisely, the work introduces structural stochastic concepts and fundamental stochastic results for the formulation of stochastic models of various global risk governance operations particularly valuable in proactive treatment of several groups of global risks.
988 _aSpringer_Robotics_2022
650 7 _2embne
_9673359
_aAnálisis estocástico
650 7 _2embne
_9154176
_aEvaluación del riesgo
650 7 _2embne
_aInteligencia artificial
_9413115
700 1 _aArtikis, Constantinos
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9683363
776 0 8 _iPrinted edition:
_z9783030956905
776 0 8 _iPrinted edition:
_z9783030956929
776 0 8 _iPrinted edition:
_z9783030956936
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-95691-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
_n0
998 _b04/2022
_dz
_esc
_zSI