The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

banks are one of the most important financial sectors in order to the economic development of each country. certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. sometimes the performance of banks must be measured in the presence of undesirable and vague factors. for these reasons in the current paper a procedure based on data envelopment...

one of the important issues of today's world is efficiency measurement of different organizations and the comparison between their units. on the other hand, banks play pivotal role in improvement of economic signals in each country. therefore, considering this role and the number of banks in iran, efficiency measurement of banks becomes important. the main goal of this paper is studying th...

The importance of supplier selection is nowadays highlighted more than ever as companies have realized that efficient supplier selection can significantly improve the performance of their supply chain. In this paper, an integrated model that applies Data Envelopment Analysis (DEA) and Support Vector Machine (SVM) is developed to select efficient suppliers based on their predicted efficiency sco...

Data envelopment analysis (DEA) as introduced by Charnes et al [3] is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency sc...

Data Envelopment Analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of Decision Making Units (DMUs). Conventional DEA methods treat DMUs as ‘‘black boxes’’, focusing entirely on their relative efficiencies. We propose an efficient two-stage fuzzy DEA model to calculate the efficiency scores for a DMU and its sub-DMUs. We use the Stackelberg ...

Performance evaluation enables decision makers (DMs) to have a better view about the weaknesses and strengths of leading units improve efficiencies as crucial goal. Data envelopment analysis (DEA) is most popular technique measure performance efficiency making (DMUs). However, conventional DEA unable consider uncertainty input output data in evaluations. In this study, order address data, robus...

The failure mode and effects analysis (FMEA) is a widely used analytical technique that helps to identify and reduce the risks of failure in a system, component, or process. One important issue of FMEA is the determination of the risk priorities of failure modes. Risk ranking is produced in order to prioritize the focus on each of the failure modes that are identified. In this study, we applied...

BACKGROUND The Dog erythrocyte antigen (DEA) 1 blood group system was thought to contain types DEA 1.1 and 1.2 (and possibly 1.3 [A3]). However, DEA 1.2+ dogs are very rare and newer typing methods reveal varying degrees of DEA 1 positivity. OBJECTIVES To assess if variation in DEA 1 positivity is because of quantitative differences in surface antigen expression. To determine expression patte...