In this article we introduce the notion of different types of statistically convergent and statistically null fuzzy real-valued double sequence spaces. We study their different properties like solidness, symmetric, convergence free, sequence algebra etc. The fuzzy real-valued Cesàro summable double sequence space is introduced. A relation between strongly p-Cesàro summability and bounded statis...

We consider the generalized method-of-case (GMC) inference scheme with fuzzy antecedents, which has been introduced by Da in [1]. We show that when the fuzzy numbers involved in the observation part of the scheme have continuous membership functions; and the t-norm, t-conorm used in the definition of the membership function of the conclusion are continuous, then the conclusion defined by the co...

K e y w o r d s C o m p e n s a t o r y , Fuzzy similarity measure, Inverted wedge system, Backpropagation algorithm. 1. I N T R O D U C T I O N Recently, the neural fuzzy approach to system modeling has become a popular research topic [110]. Moreover, the neural fuzzy method possesses the advantages of both the pure neural and the fuzzy methods; it brings the low-level learning and computation...

In this paper, we propose a novel wavelet-based-CMAC (WCMAC) network for predictive image coding. The Gaussian functions of traditional CMAC are replaced by wavelet functions. In addition, properties and advantages of fuzzy TSK-model are used to modify the activation functions of CMAC for obtaining high approximation accuracy and convergent rate. The WCMAC is employed to predict differential pu...

We show that analogously to classical probability theory the conditional expectation E ( ? ~ X ) of a fuzzy random variable Y w.r.t. a fuzzy random variable X is w.r.t. a suitable metric the best approximation o f ? by measurable functions ofX. Furthermore, several linear regression functions, i.e. best approximation of ? by linear functions o f z and examples for random LR-fuzzy numbers and Ga...

it is well known fact that binary relations are generalized mathematical functions. contrary to functions from domain to range, binary relations may assign to each element of domain two or more elements of range. some basic operations on functions such as the inverse and composition are applicable to binary relations as well. depending on the domain or range or both are fuzzy value fuzzy set, i...

classical deterministic inventory models consider the demand rate to be either constant or time-dependent but independent from the stock status. however, for a certain type of inventory, the demand rate may be in-fluenced by the stock level. also in many real-life problems, some products such as fruits, vegetables, phar-maceuticals and volatile liquids continuously deteriorate to evaporation, o...

By applying the recurrent functional neural fuzzy network (RFNFN) and a novel evolutionary learning algorithm this study presents an evolutionary neural fuzzy network (NFN). The proposed new evolutionary learning algorithm is based on an effective combination of the modified differential evolution (MDE) and cultural algorithm, which is called the cultural-based MDE (CMDE) method. After the four...

pedomodels have become a popular topic in soil science and environmentalresearch. they are predictive functions of certain soil properties based on other easily orcheaply measured properties. the common method for fitting pedomodels is to use classicalregression analysis, based on the assumptions of data crispness and deterministic relationsamong variables. in modeling natural systems such as s...

In this paper the concept of strongly (λM )p − Cesáro summability of a sequence of fuzzy numbers and strongly λM− statistically convergent sequences of fuzzy numbers is introduced. Keywords—Fuzzy numbers, statistical convergence, Orlicz space, gai sequence.