ZERM DEA integrated approach for Evaluation of Banks & Financial Institutes in Stock Exchange Abstract   The purpose of this study is to evaluate efficiency and effectiveness of banks, financial and credit institutes active in stock and superstock exchange organizations using new Fuzzy DEA model which is the modified, improved and enhanced version of Russellu0027s measurement model. In order to make it more efficient, we used the Znumbers theory through which the calculations of uncertainty in the decisionmaking process can be showed more accurately. To do so, the literature of this industry and financial data of the research companies during 2012 to 2017 were initially overviewed and 16 indicators (indicesindexes) and the main criteria related to their performance evaluation were selected. Afterward, the productivity of banks and financial and credit institutions in different levels of xcexb1xe2x80xafxe2x88x92xe2x80xafcut were specified and compared using integrated approach of ERM and calculations of Znumbers as well as considering opinions provided by the financial experts with possibility of concurrent evaluation of the efficiency and effectiveness in a model.

Clustering method for production of Znumber based ifthen rules Abstract   Application of clustering algorithms to extract or summarize data from large data sets is a straightforward and effective approach. Sometimes data sets are not only large in size but also include imprecise and partially reliable pieces of information of probabilistic and possibilistic (fuzzy) nature. Information of this kind is referred to as bimodal information. There is a need to summarize such data into a compact set of human tractable xe2x80x9cIfThenxe2x80x9d rules, being a result of synergy of imprecision of both types. In this paper, we first present an approach to clustering with the purpose of extraction of probabilistic and fuzzy information (bimodal) categories suitable for formation of humantractable rules. The suggested clustering algorithm utilizes the FCM objective function and an evolutionary algorithm to produce fuzzy sets of fuzzy clusters. To form Zclusters and use them as components for the rules we exploit the relationship existing between Type2 Fuzzy and Znumber concepts. A benchmark problem and a realworld application are considered to demonstrate the usefulness of the proposed approach.