000 03827nam a22005535i 4500
001 978-1-4614-4250-9
003 DE-He213
005 20140220082814.0
007 cr nn 008mamaa
008 120925s2013 xxu| s |||| 0|eng d
020 _a9781461442509
_9978-1-4614-4250-9
024 7 _a10.1007/978-1-4614-4250-9
_2doi
050 4 _aQ295
050 4 _aQA402.3-402.37
072 7 _aGPFC
_2bicssc
072 7 _aSCI064000
_2bisacsh
072 7 _aTEC004000
_2bisacsh
082 0 4 _a519
_223
100 1 _aSirbiladze, Gia.
_eauthor.
245 1 0 _aExtremal Fuzzy Dynamic Systems
_h[electronic resource] :
_bTheory and Applications /
_cby Gia Sirbiladze.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXXII, 400 p. 26 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIFSR International Series on Systems Science and Engineering,
_x1574-0463 ;
_v28
505 0 _aFuzzy Measures and Fuzzy Statistics: Its Probability Representations -- Extended Extremal Fuzzy Measures -- Extended Extremal Fuzzy Measures on Compositional Product of Measurable Spaces -- Modeling of Extremal and Controllable Extremal Fuzzy Processes -- Identification of  Fuzzy-Integral Models of Extremal fuzzy Processes -- Optimization of Continuous Controllable Extremal Fuzzy Processes and the Choice of Decisions -- Problems of States Estimation (Filtration) of Extremal Fuzzy Processes. - Conclusions on the Parts I-VII -- Algorithms and software for Discrete Possibilistic EFDS -- Application  of the Discrete Possibilistic Model  of the EFDS in the Evaluation of  Expert Knowledge Streams -- Application: Forecasting of  Increasing Financial Risks (Credit Risks) of Georgia-based Organization (LTD-“Fractal”) by the Discrete Possibilistic EFDS’s Finite Model.-  General Conclusions -- Bibliography.
520 _aIn this book the author presents a new approach to the study of weakly structurable dynamic systems. It differs from other approaches by considering time as a source of fuzzy uncertainty in dynamic systems. It begins with a thorough introduction, where the general research domain, the problems, and ways of their solutions are discussed. The book then progresses systematically by first covering the theoretical aspects before tackling the applications. In the application section, a software library is described, which contains discrete EFDS identification methods elaborated during fundamental research of the book. Extremal Fuzzy Dynamic Systems will be of interest to theoreticians interested in modeling fuzzy processes, to researchers who use fuzzy statistics, as well as practitioners from different disciplines whose research interests include abnormal, extreme and monotone processes in nature and society. Graduate students could also find this book useful.
650 0 _aMathematics.
650 0 _aArtificial intelligence.
650 0 _aComputer simulation.
650 0 _aSystems theory.
650 0 _aOperations research.
650 1 4 _aMathematics.
650 2 4 _aSystems Theory, Control.
650 2 4 _aSimulation and Modeling.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aMeasure and Integration.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aOperation Research/Decision Theory.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461442493
830 0 _aIFSR International Series on Systems Science and Engineering,
_x1574-0463 ;
_v28
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-4250-9
912 _aZDB-2-SMA
999 _c95097
_d95097