Mohammad Mehdi Korjani

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Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the social scientist Prof. Charles C. Ragin. fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that describe how(More)
Fuzzy set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It has recently been described as a collection of 13 steps [3]. In this paper we focus on how to speed up some of the computationally intensive steps of fsQCA and how to use the speed-up equations to obtain(More)
—The main contribution of this paper is to develop a Perceptual Computer for Fuzzy Love Selection problem. This is a problem of ranking all members (alternatives) in an individual list in order of preference. Uncertainty of the individual about criteria scores and weights assigned to each alternative is handled by means of Perceptual Computer. This paper(More)
Fuzzy set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It contains 13 steps which are mathematically described in [2]. In this paper we focus on the validation of fsQCA by using it to obtain a granular (linguistic) description of a function as a collection of(More)
This paper presents a very efficient method for establishing nonlinear combinations of variables from small to big data for use in later processing (e.g., regression, classification, etc.). Variables are first partitioned into subsets each of which has a linguistic term (called a causal condition) associated with it. Our Causal Combination Method uses fuzzy(More)