Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy Sets and Systems - Fuzzy Numbers
Fuzzy systems theory and its applications
Fuzzy systems theory and its applications
Markov chains with a transition possibility measure and fuzzy dynamic programming
Fuzzy Sets and Systems
Fuzzy integral in multicriteria decision making
Fuzzy Sets and Systems - Special issue on fuzzy information processing
Exponential possibility regression analysis
Fuzzy Sets and Systems - Special issue on fuzzy information processing
Fuzzy Sets and Systems
Most typical values for fuzzy sets
Fuzzy Sets and Systems
Constructing fuzzy measures in expert systems
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
A limit theorem in dynamic fuzzy systems with a monotone property
Fuzzy Sets and Systems
A fuzzy relational equation in dynamic fuzzy systems
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Special issue on fuzzy modeling and dynamics
Fuzzy Sets and Systems
On the observability of fuzzy dynamical control systems (I)
Fuzzy Sets and Systems
Fuzzy dynamical systems—inverse and direct spectra
Fuzzy Sets and Systems
Generators of fuzzy dynamical systems
Fuzzy Sets and Systems
Fuzzy stochastic differential systems
Fuzzy Sets and Systems
Soft Computing for Risk Evaluation and Management: Applications in Technology, Environment and Finance
Architecture of Systems Problem Solving
Architecture of Systems Problem Solving
Weighted fuzzy averages in fuzzy environment: part I. Insufficient expert data and fuzzy averages
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Restored fuzzy measures in expert decision-making
Information Sciences: an International Journal
Bellman's optimality principle in the weakly structurable dynamic systems
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
Using a minimal fuzzy covering in decision-making problems
Information Sciences: an International Journal
ACACOS'11 Proceedings of the 10th WSEAS international conference on Applied computer and applied computational science
Prediction problem's solution for the finite possibilistic model of expert knowledge streams
ACMIN'12 Proceedings of the 14th international conference on Automatic Control, Modelling & Simulation, and Proceedings of the 11th international conference on Microelectronics, Nanoelectronics, Optoelectronics
Fuzzy modeling of minimal crediting risks in investment decisions
ACMIN'12 Proceedings of the 14th international conference on Automatic Control, Modelling & Simulation, and Proceedings of the 11th international conference on Microelectronics, Nanoelectronics, Optoelectronics
Hi-index | 0.00 |
This work deals with the problems of the Continuous Extremal Fuzzy Dynamic System (CEFDS) optimization and briefly discusses the results developed by Sirbiladze (Int J Gen Syst 34(2):107---138, 2005a; 34(2):139---167, 2005b; 34(2):169---198, 2005c; 35(4):435---459, 2006a; 35(5):529---554, 2006b; 36(1): 19---58, 2007; New Math Nat Comput 4(1):41---60, 2008a; Mat Zametki, 83(3):439---460, 2008b). The basic properties of extended extremal fuzzy measures and Sugeno's type integrals are considered and several variants of their representation are given. Values of extended extremal conditional fuzzy measures are defined as a levels of expert knowledge reflections of CEFDS states in the fuzzy time intervals. The notions of extremal fuzzy time moments and intervals are introduced and their monotone algebraic structures that form the most important part of the fuzzy instrument of modeling extremal fuzzy dynamic systems are discussed. A new approach in modeling of CEFDS is developed. Applying the results of Sirbiladze (Int J Gen Syst 34(2) 107---138, 2005a; 34(2):139---167, 2005b), fuzzy processes with possibilistic uncertainty, the source of which are expert knowledge reflections on the states on CEFDS in extremal fuzzy time intervals, are constructed (Sirbiladze in Int J Gen Syst 34(2):169---198, 2005c). The dynamics of CEFDS's is described. Questions of the ergodicity of CEFDS are considered. A fuzzy-integral representation of a continuous extremal fuzzy process is given. Based on the fuzzy-integral model, a method and an algorithm are developed for identifying the transition operator of CEFDS. The CEFDS transition operator is restored by means of expert data with possibilistic uncertainty, the source of which is expert knowledge reflections on the states of CEFDS in the extremal fuzzy time intervals. The regularization condition for obtaining quasi-optimal estimator of the transition operator is represented by the theorems. The corresponding calculating algorithm is provided. The results obtained are illustrated by an example in the case of a finite set of CEFDS states.