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In this paper, a novel group decision-making method is proposed based on the weighted SBM model of data envelopment analysis (DEA) and intuitionistic fuzzy preference relations (IFPRs). Indeed, for the data fuzzy numbers set, the main aim of this study is to measure the efficiency of different alternatives in the framework of IFPRs by the weighted SBM model. In this regard, first, the interval transform function is used to convert IFPRs into interval multiplicative preference relations. After calculating the efficiency, the optimal weights for each IFPR are identified using two cross-efficiency models to obtain the normalized intuitionistic fuzzy priority vector. Then, an algorithm for group decision-making is proposed using a goal programming, SBM model with ideal weights and IFPRs to rank the units. Finally, the model is implemented numerically, and the results are also compared with other models, including the output-oriented Charnes-Cooper-Rhodes) CCR (and basic Banker-Charnes-Cooper (BCC) models. It is shown that the proposed method outperforms traditional CCR and BCC models and provides more reasonable results.
The present paper is an attempt to describe the writing pattern of Hindi language texts with the help of mathematical techniques. The analyses of the selected texts have been done by the use of the roman alphabet transforms of the texts. An attempt has been made to characterize texts mathematically on the basis of the presence of different letters of alphabets and by means of quantification of the texts with the help of entropy of pattern of occurrence of letters. The characteristic curves have been formed depending on the presence of different letters in the corresponding roman text and the entropy of the pattern of occurrence of letters has also been calculated. The determined curve and the entropic extent have also been compared with the same type of curve and entropies for two texts in the English language. The work has significance in the process of language identification, as the determined curve and the specific entropic quantitative measure can be considered useful tools.