In interval type-2 fuzzy logic controllers (IT2-FLCs), the output processing includes type reduction and defuzzification. Recently, researchers have proposed many efficient type reduction algorithms, but there are no effective schemes to improve the output of defuzzification. This paper presents a geneticalgorithm-based type reduction algorithm, which reduces the type of an interval type-2 fuzz...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...

nowadays, the problem of the flexibility in any organization has essential importance and the associated investigation with the organizational efficiency and performance is considered. in real-world situation, the process of decision making is often based on linguistic and mental data, so applying fuzzy logic in modeling at this point of view is convenient. in this paper, a fuzzy approach is ap...

Fuzzy histograms are a fuzzy generalization of ordinary crisp histograms. In this paper, fuzzy histograms are analyzed statistically and are compared with other nonparametric density estimators. It turns out that fuzzy histograms can be used to combine a high level of statistical efficiency with a high level of computational efficiency.

Data Envelopment Analysis (DEA) is a technique for measuring the efficiency of a set of Decision Making Units (DMUs) with common data, but in general it is not practical. This paper presents a framework where DEA is used to measure overall profit efficiency with fuzzy data. Specifically, it is shown that as the inputs, outputs and price vectors are fuzzy numbers, the DMUs cannot be easily evalu...

  A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of th...

kim and bishu (fuzzy sets and systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. we show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...

in this paper, the variational iteration method for solving nth-order fuzzy integro differential equations (nth-fide) is proposed. in fact the problem is changed to the system of ordinary fuzzy integro-differential equations and then fuzzy solution of nth-fide is obtained. some examples show the efficiency of the proposed method.