Mohammad Mehdi Korjani

Learn More
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)
—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 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)
Recently, several recurrent neural networks for solving constraint optimization problems were developed. In this paper, we propose a novel approach to the use of a projection neural network for solving real time identification and control of time varying systems. In addition to low complexity and simple structure, the proposed neural network can solve wider(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)
In our study, we tried to develop our teams in such a way that machine learning techniques and advanced artificial intelligence tools have the main role in improving skills and increasing team performance. We consider soccer simulation platform as an uncertain and dynamic environment, so we develop learning algorithms according to this important feature and(More)