Fuzzy risk analysis, as a powerful tool to address uncertain information, can provide an appropriate method for risk analysis. However, the previous fuzzy risk analysis methods still have some weaknesses. To overcome the weaknesses of existing fuzzy risk analysis methods, a novel method for ranking generalized fuzzy numbers is proposed for addressing fuzzy risk analysis problems. In the propose...

recently, phiangsungnoen et al. [j. inequal. appl. 2014:201 (2014)] studied fuzzy mappings in the framework of hausdorff fuzzy metric spaces.following this direction of research, we establish the existence of fixed fuzzy points of fuzzy mappings. an example is given to support the result proved herein; we also present a coincidence and common fuzzy point result. finally, as an application of ou...

the certainty assumption that is used in economic analysis, althouth is easier in analysis, may be but not logical because in most projects time is playing a key role. in this time horizon the amount of income and future costs affecting by factors that are not managable by investors and can not to be forecasted. therefore in practice usually there is a gap between forecased and real variables. ...

The paper focuses on the fuzzy extensions of two data analysis methods, namely the fuzzy cluster analysis and the fuzzy interpolation of spatial data (the so-called fuzzy kriging) and their suitability for ecological applications. Both extensions utilize exact (crisp) measurement data as well as imprecise data defined as fuzzy numbers or fuzzy vectors. Fuzzy clustering of fuzzy data (conical fu...

in this paper, we propose a new residual analysis method using fourier series transform into fuzzy time series model for improving the forecasting performance. this hybrid model takes advantage of the high predictable power of fuzzy time series model and fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

data envelopment analysis (dea) has been proven as an efficient technique to evaluate the performance of homogeneous decision making units (dmus) where multiple inputs and outputs exist. in the conventional applications of dea, the data are considered as specific numerical values with explicit designation of being an input or output. however, the observed values of the data are sometimes imprec...

Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability.  The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability is a way to present the reliability function uncertainly using fuzzy parameters. In the proposed...

This paper is a survey of fuzzy set theory applied in cluster analysis. These fuzzy clustering algorithms have been widely studied and applied in a variety of substantive areas. They also become the major techniques in cluster analysis. In this paper, we give a survey of fuzzy clustering in three categories. The first category is the fuzzy clustering based on fuzzy relation. The second one is t...