scholarly journals Trends in Fuzzy Statistics

2016 ◽  
Vol 32 (3) ◽  
pp. 239-257 ◽  
Author(s):  
S. Mahmoud Taheri
Keyword(s):  
Bayesian Statistics ◽  
Statistical Methods ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Regression ◽  
Hypotheses Testing ◽  
Fuzzy Statistics ◽  
Fuzzy Hypotheses

After introducing and developing fuzzy set theory, a lot of studies have been done to combine statistical methods and fuzzy set theory. Thisworks, called fuzzy statistics, have been developed in some branches.In this article we review essential works on fuzzy estimation, fuzzy hypotheses testing, fuzzy regression, fuzzy Bayesian statistics, and some relevant fields.

Design of an Aircraft Tire: A Study in Modeling Uncertainty

1992 ◽  
Author(s):  
S. Vadde ◽  
S. Swadi ◽  
N. Bhattacharya ◽  
F. Mistree ◽  
J. K. Allen
Keyword(s):  
Decision Support ◽  
Bayesian Statistics ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Model Uncertainty ◽  
Design Problems ◽  
Modeling Uncertainty ◽  
Imprecise Information ◽  
Uncertainty In Design

Abstract During the early stages of project initiation, the information available to a designer may be uncertain (imprecise or stochastic). In response to this need, two extensions of the crisp compromise Decision Support Problem using fuzzy set theory and Bayesian statistics are developed to model uncertainty in design problems. The fuzzy compromise DSP is used to model imprecise information and the Bayesian compromise DSP is used to model stochastic information. The design of an aircraft tire is used as an illustrative example.

scholarly journals A Review on Fuzzy Control Charts for Monitoring Attribute Data

2012 ◽  
Vol 159 ◽  
pp. 23-28 ◽  
Author(s):  
Seyed Mojtaba Zabihinpour Jahromi ◽  
Abbas Saghaei ◽  
Mohd Khairol Anuvar Mohd Ariffin
Keyword(s):  
Fuzzy Control ◽  
Statistical Method ◽  
Statistical Methods ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Control Charts ◽  
Average Run Length ◽  
Attribute Data ◽  
Fuzzy Methods

Up to now, several methods have been proposed for monitoring processes with attribute data. These methods can be categorized into two major group; statistical methods and fuzzy methods. In this paper current fuzzy methods are introduced and the performance of fuzzy methods and statistical methods are compared together based on the Average Run Length (ARL). The comparison shows that the statistical method has the best performance. We show the necessity of using fuzzy method in case of attribute data. Then the critiques towards fuzzy methods are reviewed which show the usage of fuzzy set theory in these methods have some restriction. As a result we indicate a study gap about the usage of fuzzy set theory for monitoring processes with attribute data and at the end some guideline for the next study are proposed.

scholarly journals Application of Fuzzy Set Theory and DEA Model to Evaluating Production Efficiency for Taipei City Bus Company

2001 ◽  
Vol 5 (3) ◽  
pp. 128-138 ◽  
Author(s):  
Gwo-Hshiung Tzeng ◽  
◽  
Cheng-Min Feng ◽  
Chao-Chung Kang
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Production Efficiency ◽  
Fuzzy Numbers ◽  
Fuzzy Regression ◽  
Dea Model ◽  
City Bus ◽  
Stochastic Dea ◽  
Taipei City

The purpose of this paper is to present a performance evaluation model for forecasting production efficiency for Decision Making Units (DMUs). This model is based on the fuzzy set theory, fuzzy regression, and the DEA model. A stochastic DEA approach has been proposed and used widely to analyze the performance of the uncertain input or output data, but this approach requires large data samples and assumes probability distribution in measurement error terms. The concept of fuzzy numbers was seldom considered, although the stochastic DEA approach can be used for prediction. This paper integrates fuzzy regression and fuzzy DEA as one model. The results of this research show that the model developed in this paper is applicable to evaluate the "reform policy for passenger loading operations" currently undertaken by the Taipei City Bus Company. Based on this study, the integration of fuzzy numbers, fuzzy regression, and the DEA model can be applied to evaluate production efficiency of the city bus company for the short-term future.

Estimating construction waste generation in residential buildings: A fuzzy set theory approach in the Brazilian Amazon

2020 ◽  
Vol 265 ◽  
pp. 121779 ◽  
Author(s):  
Luiz Maurício Furtado Maués ◽  
Brisa do Mar Oliveira do Nascimento ◽  
Weisheng Lu ◽  
Fan Xue
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Residential Buildings ◽  
Brazilian Amazon ◽  
Theory Approach ◽  
Waste Generation ◽  
Construction Waste
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