This study proposes a novel neural-network-based fuzzy group forecasting model for foreign exchange rates prediction. In the proposed model, some single neural network models are first used as predictors for foreign exchange rates prediction. Then these single prediction results produced by each single neural network models are fuzzified into some fuzzy prediction representations. Subsequently,...

In reliability optimization problems diverse situation occurs due to which it is not always possible to get relevant precision in system reliability. The imprecision in data can often be represented by triangular fuzzy numbers. In this manuscript, we have considered different fuzzy environment for reliability optimization problem of redundancy. We formulate a redundancy allocation problem for a...

In this paper, we present a new method for ranking generalized fuzzy numbers for dealing with fuzzy risk analysis problems. The proposed method considers the defuzzified values, the heights and the spreads of generalized fuzzy numbers, simultaneously, for ranking generalized fuzzy numbers. It gets better ranking results to rank generalized fuzzy numbers than the existing methods. We also apply ...

the problem of hypothesis testing with a nuisance parameter is considered. two methods forusing fuzzy knowledge on the nuisance parameter to test hypotheses are suggested. these methods areneither a pure classical nor a pure bayesian approach to hypothesis testing, but rather related to both. afew known examples and their applications, which cannot be studied by the parametric statisticalmethod...

The paper presents second author’s step toward building quite new theory of fuzzy signals. Before, in the first step author defined fuzzy Fourier transform. Here, an approach to description of fuzzy correlation functions is proposed. New definitions, called later fuzzy correlation and defuzzified correlation are proposed for fuzzy signals. The definitions are based on new concepts of the class ...

The purpose is to establish a logistics supplier evaluation and selection model for green supply chain, which can effectively take into account the environmental problems, while enterprise economy developing. index system established under background of based on fuzzy theory multicriteria decision-making theory. competitiveness innovatively introduced system. Moreover, hybrid method deficiency ...

This paper investigates the economic order quantity (EOQ) — based inventory model for a retailer under two levels of trade credit to reflect the supply chain management situation in the fuzzy sense. It is assumed that the retailer maintains a powerful position and can obtain the full trade credit offered by the supplier yet the retailer just offers a partial trade credit to customers. The deman...

The Fuzzy State Space algorithm (FSSA) is the main feature in the development of the Fuzzy State Space Model (FSSM) for solving inverse problems in multivariable dynamic systems. Traditionally, such inverse problems have been addressed by repeated simulation of forward problems, which requires excessive computer time and thus can be very costly. In the formulation of the FSSA, the uncertain val...

Two-string fuzzy inference consists of two separate inference mechanisms: One conventional fuzzy inference system that processes recommending rules, as well as a mechanism for processing negative rules, which prevent the system from outputting their associated values when their premise is fulfilled. Two-string inference has valuable applications in pattern recognition and control tasks. We pres...

This paper deals with center of sum defuzzification method via a computationally attractive method, called transformation function method. A technique for deriving the transformation functions for output fuzzy sets with trapezoidal membership functions has been introduced. It is shown that this method enormously reduces number of mathematical operations and amount of memory space required to co...