This paper proposes a fuzzy channel allocation controller (FCAC) for hierarchical cellular systems. The FCAC mainly contains a fuzzy channel allocation processor (FCAP) which is designed to be in a two-layer architecture that consists of a fuzzy admission threshold estimator in the first layer and a fuzzy channel allocator in the second layer. The FCAP chooses the handoff failure probability, d...

In this paper, we propose a scalar variable formation of fuzzy regression model based on the axiomatic credibility measure foundation. The fuzzy estimation for fuzzy regression coefficients is investigated. A general M-estimation criterion is developed under Maximum Fuzzy Uncertainty Principle, which resulted in weighted Normal equation with adjusted term for M-estimator of the regression coeff...

In this paper, we develop fuzzy, possibilistic hypothesis tests for testing crisp hypotheses a distribution parameter from data. these tests, fuzzy statistics are used, which produced by the possibility of estimated parameter, constructed known confidence intervals. The results in much better agreement with than ones respective popular book on statistics, uses critical values. We also present a...

Software estimation has been one of the biggest challenges in Computer Science for the last decades. This practice is essential for research and development companies, since it can provide cost and deadline forecasting, for example. Most of the traditional techniques such as function points, regression models, COCOMO, etc, require a long-term estimation process, which is unworkable for greatly ...

M-estimators can be seen as a special case of robust clustering algorithms. In this paper, we present the reversed direction and show that clustering algorithms can be constructed by using M-estimators. A clever normalization is used to link the values of several M-estimator prototypes together in one clustering algorithm. A variety of M-estimators and several normalization strategies are used ...

In this paper, the extension principle is used in order to fuzzify location and scale estimators when used on fuzzy numbers. First, fuzzy nonlinear means, such as arithmetic, harmonic, geometric and fuzzy L p mean are deened as extensions of the corresponding crisp means. Fuzzy maximum and minimum operators are used to deene order statistics of fuzzy numbers. Fuzzy L location and scale estimato...

This paper proposes a new method for uniformly minimum variance unbiased fuzzy point estimation. For this purpose we make use of a uniformly minimum variance unbiased estimator and we develop this new method for a fuzzy random sample X̃1, . . . , X̃n is induced by X1, . . . , Xn on the same probability space. Zusammenfassung: In diesem Aufsatz schlagen wir eine neue Methode vor, um einen unverzer...

introduced and applied to the problems of signal restoration. A fuzzy approach for system identification and state estimation is developed. The estimated values obtained from the fuzzy model are in the form of fuzzy numbers which present the possibility of the system structure. Both L-R and symmetric triangular type membership functions are employed to derive the fuzzy-data based estimator (FBE...

We propose a fuzzy-neural modeling approach for automatically constructing a fuzzy-neural model from a set of input-output data. The proposed approach consists of two phases, structure identification and parameter identification. In the structure identification phase, rough TSK fuzzy rules are extracted through a clustering algorithm. Then a fuzzy neural network is built in the parameter identi...