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008 150903s2011 xxk| o |||| 0|eng d
020 _a9780857297907
_99780857297907
024 7 _a10.1007/9780857297907
_2doi
035 _avtls000333993
039 9 _a201509030243
_bVLOAD
_c201404300252
_dVLOAD
_y201402041137
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQ334-342
100 1 _aMarwala, Tshilidzi.
_eautor
_9305386
245 1 0 _aMilitarized Conflict Modeling Using Computational Intelligence /
_cby Tshilidzi Marwala, Monica Lagazio.
264 1 _aLondon :
_bSpringer London,
_c2011.
300 _axviii, 254 páginas
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aAdvanced Information and Knowledge Processing,
_x1610-3947
500 _aSpringer eBooks
520 _aMilitarized Conflict Modeling Using Computational Intelligence examines the application of computational intelligence methods to model conflict. Traditionally, conflict has been modeled using game theory. The inherent limitation of game theory when dealing with more than three players in a game is the main motivation for the application of computational intelligence in modeling conflict. Militarized interstate disputes (MIDs) are defined as a set of interactions between, or among, states that can result in the display, threat or actual use of military force in an explicit way. These interactions can result in either peace or conflict. This book models the relationship between key variables and the risk of conflict between two countries. The variables include Allies which measures the presence or absence of military alliance, Contiguity which measures whether the countries share a common boundary or not and Major Power which measures whether either or both states are a major power. Militarized Conflict Modeling Using Computational Intelligence implements various multi-layer perception neural networks, Bayesian networks, support vector machines, neuro-fuzzy models, rough sets models, neuro-rough sets models and optimized rough sets models to create models that estimate the risk of conflict given the variables. Secondly, these models are used to study the sensitivity of each variable to conflict. Furthermore, a framework on how these models can be used to control the possibility of peace is proposed. Finally, new and emerging topics on modelling conflict are identified and further work is proposed.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aLagazio, Monica.
_eautor
_9305387
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780857297891
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-85729-790-7
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c280460
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