Titlebook: Extremal Fuzzy Dynamic Systems; Theory and Applicati Gia Sirbiladze Book 2013 Springer Science+Business Media, LLC 2013 Dynamic Systems The

祖?zhèn)髫?cái)產(chǎn)

Contributions to Management Sciencemposition extremal monotone measures. Several variants of their representations are given. The notion of .-composition over extremal monotone measures is introduced, and some algebraic properties of the corresponding structures, which form the most important part of the fuzzy instrument of modeling extremal fuzzy dynamic systems, are discussed.

小卒

GLIDE

https://doi.org/10.1007/978-3-540-77303-0tion of problems of analysis and synthesis of incomplete and expert information in the setting of many anomalous, extreme, and complex global processes. The prediction and determination of possible scenarios of the evolution of these processes have become highly important. Today, problems of simulat

Allege

Nadine Kammerlander,Reinhard Prüglions (MSR) of several monotone measures are presented. These include Choquet capacities of order two (in general), Dempster–Shafer belief structure, Sugeno λ-measures, and possibility measure. Connections between the CBR and MSR are considered. Analogously to CBR, theorems of existence of Choquet ca

voluble

Funding Innovation and Entrepreneurship,emal monotone measures, several transformation theorems are proved for extended lower and upper Sugeno integrals. Extended extremal conditional monotone measures are defined. The notions of extremal fuzzy time moments and intervals are introduced, and their monotone algebraic structures, which form

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legislate

畸形

https://doi.org/10.1057/9781137268556 stationary discrete extremal fuzzy dynamic systems (EFDS). The EFDS “input–output” operator is restored by means of expert knowledge data with possibilistic uncertainty, the source of which is extremal fuzzy time intervals (.). The regularization conditions for obtaining quasi-optimal estimates are

judiciousness

nitroglycerin

Innovation in Language Learning and Teaching systems, i.e., of the so-called extremal fuzzy dynamic systems constructed in Chap. 5. In the present chapter, problems of an optimal filtering of continuous as well as of discrete extremal fuzzy processes are solved by means of “past” evaluating information. Sufficient conditions are established f