000 | 03827nam a22005535i 4500 | ||
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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 |
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024 | 7 |
_a10.1007/978-1-4614-4250-9 _2doi |
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050 | 4 | _aQ295 | |
050 | 4 | _aQA402.3-402.37 | |
072 | 7 |
_aGPFC _2bicssc |
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072 | 7 |
_aSCI064000 _2bisacsh |
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072 | 7 |
_aTEC004000 _2bisacsh |
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082 | 0 | 4 |
_a519 _223 |
100 | 1 |
_aSirbiladze, Gia. _eauthor. |
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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. |
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300 |
_aXXII, 400 p. 26 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aIFSR International Series on Systems Science and Engineering, _x1574-0463 ; _v28 |
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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 |