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001444118 001__ 1444118
001444118 003__ OCoLC
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001444118 019__ $$a1294921405$$a1295277331$$a1296427580$$a1296666851
001444118 020__ $$a9783030956912$$q(electronic bk.)
001444118 020__ $$a3030956911$$q(electronic bk.)
001444118 020__ $$z9783030956905
001444118 020__ $$z3030956903
001444118 0247_ $$a10.1007/978-3-030-95691-2$$2doi
001444118 035__ $$aSP(OCoLC)1294831337
001444118 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dDKU$$dEBLCP$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCQ
001444118 049__ $$aISEA
001444118 050_4 $$aHB615$$b.A75 2022
001444118 08204 $$a368$$223
001444118 1001_ $$aArtikis, Panagiotis,$$eauthor.
001444118 24510 $$aRandom contractions in global risk governance /$$cPanagiotis T. Artikis, Constantinos T. Artikis.
001444118 264_1 $$aCham :$$bSpringer,$$c[2022]
001444118 264_4 $$c©2022
001444118 300__ $$a1 online resource.
001444118 336__ $$atext$$btxt$$2rdacontent
001444118 337__ $$acomputer$$bc$$2rdamedia
001444118 338__ $$aonline resource$$bcr$$2rdacarrier
001444118 347__ $$atext file$$bPDF$$2rda
001444118 4901_ $$aLearning and analytics in intelligent systems ;$$vvolume 27
001444118 504__ $$aIncludes bibliographical references.
001444118 5050_ $$aChapter 1: Stochastic Concepts in Global Risk Governance Operations -- Chapter 2: Formulation of a Stochastic Model -- Chapter 3: Random Contraction Representation for a Stochastic Model -- Chapter 4: Interpretation of a Stochastic Model in Global Risk Governance. .
001444118 506__ $$aAccess limited to authorized users.
001444118 520__ $$aThis book contributes to the area of ongoing global risks and the area of forthcoming global risks, particularly necessary for the implementation of very important interdisciplinary research activities. Global risks are defined in this study as having a global geographical scope, an inter-industrial presence, and exceptionally critical stages of economic and social participation that necessitate a major multi-stakeholder input. In addition, global risks demand an extremely extensive priority in decision-making allowance. The theoretical and practical results of this work are strongly connected to several quite useful factors. The present work mainly concentrates on the contribution of probability theory in the advancement of the practical applicability of global risk governance. More precisely, the work introduces structural stochastic concepts and fundamental stochastic results for the formulation of stochastic models of various global risk governance operations particularly valuable in proactive treatment of several groups of global risks.
001444118 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 16, 2022).
001444118 650_0 $$aRisk.
001444118 650_0 $$aStochastic models.
001444118 650_6 $$aRisque.
001444118 650_6 $$aModèles stochastiques.
001444118 655_0 $$aElectronic books.
001444118 7001_ $$aArtikis, Constantinos,$$eauthor.
001444118 77608 $$iPrint version: $$z3030956903$$z9783030956905$$w(OCoLC)1290429707
001444118 830_0 $$aLearning and analytics in intelligent systems ;$$vv. 27.
001444118 852__ $$bebk
001444118 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-95691-2$$zOnline Access$$91397441.1
001444118 909CO $$ooai:library.usi.edu:1444118$$pGLOBAL_SET
001444118 980__ $$aBIB
001444118 980__ $$aEBOOK
001444118 982__ $$aEbook
001444118 983__ $$aOnline
001444118 994__ $$a92$$bISE