In this paper, we will illustrate the F-transform based on generalized fuzzy partitions as a tool for expectile smoothing. This allows to represent a time series in terms of a fuzzy-valued function whose level-cuts are modeled by F-transform and estimated by expectile regression. The proposed methodology is illustrated on real economic and …nancial time series. Keywords: Fuzzy Transform, Expect...

we have the crisp vector → PQ= (y(1)−x(1),y(2)−x(2), . . . ,y(n)−x(n)) in a pseudo-fuzzy vector space Fn p (1)= {(a(1),a(2), . . . ,a(n))1∀(a(1),a(2), . . . ,a(n))∈Rn}. There is a one-to-one onto mapping P = (x(1),x(2), . . . ,x(n)) ↔ P̃ = (x(1),x(2), . . . , x)1. Therefore, for the crisp vector → PQ, we can define the fuzzy vector → P̃ Q̃= (y(1)− x(1),y(2)−x(2), . . . ,y(n)−x(n))1 = Q̃ P̃ . Let the...

we have the crisp vector → PQ= (y(1)−x(1),y(2)−x(2), . . . ,y(n)−x(n)) in a pseudo-fuzzy vector space Fn p (1)= {(a(1),a(2), . . . ,a(n))1∀(a(1),a(2), . . . ,a(n))∈Rn}. There is a one-to-one onto mapping P = (x(1),x(2), . . . ,x(n)) ↔ P̃ = (x(1),x(2), . . . , x)1. Therefore, for the crisp vector → PQ, we can define the fuzzy vector → P̃ Q̃= (y(1)− x(1),y(2)−x(2), . . . ,y(n)−x(n))1 = Q̃ P̃ . Let the...

This paper deals with an impulsive stochastic fuzzy cellular neural networks with both time-varying and infinite distributed delays. Based on M-matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and global exponential p−stability of the equilibrium point for the addressed impulsive stochastic fuzzy cellular neural network wit...

Fuzzy neural networks have been successfully applied to generate predictive rules for stocks forecasting. This paper presents a methodology for forecasting S&P 500 index based on the neural network with weighted fuzzy membership functions (NEWFM) and time series of S&P 500 index based on the defuzzyfication of weighted average method (The fuzzy model suggested by Takagi and Sugeno in 1985). NEW...

PURPOSE To quantify the impact of diagnostic confidence on radiological diagnosis with a fuzzy logic-based method. MATERIALS AND METHODS Twenty-two oncologic patients with 20 cysts and 30 metastases ≤1 cm in size found at 64-row computed tomography were included. Two readers (R1/R2) expressed diagnoses as a subjective level of confidence P(d) in malignancy within the interval [0,1] rather tha...

The paper deals with special types of $L$-ordered sets, $L$-fuzzy complete lattices, and fuzzy directed complete posets.First, a theorem for constructing monotone maps is proved, a characterization for monotone maps on an $L$-fuzzy complete lattice is obtained, and it's proved that if $f$ is a monotone map on an $L$-fuzzy complete lattice $(P;e)$, then the least fixpoint of $f$ is meet of a spe...

This paper presents the application of a modified fuzzy reasoning spiking neural P systems (MFRSN P system, for short) to fault diagnosis of metro traction power supply systems. In MFRSN P systems, three types of neurons are used to represent operation information of protection devices including protective relays and circuit breakers; a reasoning algorithm associated with MFRSN P systems is int...

This paper deals with Zadeh’s compositional rule of inference [12] under triangular norms: IF X is P AND X and Y have relation R, THEN Y is Q, where P and Q are fuzzy sets of the real line IR, R is a fuzzy relation on IR and the conclusion Q is defined via sup-T composition of P and R: μQ(y) = sup x∈IR T (μP (x), μR(x, y)), y ∈ IR. It is shown that (i) when the triangular norm T and the members...

Since it was firstly introduced by Torra and Narukawa (The 18th IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 2009, pp. 1378–1382), the hesitant fuzzy set has attracted more and more attention due to its powerfulness and efficiency in representing uncertainty and vagueness. This paper extends the classical VIKOR (vlsekriterijumska optimizacija i kompromisno resenje in serb...