Affiliations: [a]
The Institute of Cybernetic Intelligent Systems ofthe National Research Nuclear University MEPHI (IATE NRNU MEPHI), Obninsk, Russian Federation
| [b] The Department of Information Systems, Instituteof Cybernetic Intelligent Systems of the National Research NuclearUniversity MEPHI (IATE NRNU MEPHI), Obninsk –Moscow, RussianFederation
Correspondence:
[*]
Corresponding author. Boris Yatsalo, The Department of Information Systems, Institute of Cybernetic Intelligent Systems of the National Research Nuclear University MEPHI (IATE NRNU MEPHI), Obninsk –Moscow, Russian Federation. E-mail: [email protected].
Abstract: Assessing functions of fuzzy arguments and ranking of fuzzy quantities are two key steps in fuzzy modeling and Fuzzy Multicriteria Decision Analysis (FMCDA). Approximate calculations along with the use of centroid index as a defuzzification based ranking methods are a generally accepted approach to applications in the fuzzy environment. This paper presents a novel fuzzy system, F-CalcRank, which is integration of two coupled fuzzy systems: F-Calc (Fuzzy Calculator) and F-Ranking (Fuzzy Ranking). F-Calc allows assessing functions of fuzzy numbers with the use of different approaches: approximate calculations, standard fuzzy arithmetic, and transformation methods. The input values to F-Calc are fuzzy numbers with the following membership functions: triangular and trapezoidal, Gaussian, bell shape, sigmoid, and piece-wise linear continuous or upper semicontinuous membership functions of any complexity, as well as fuzzy linguistic terms of a given term set. F-Ranking system is intended for ranking of a given set of fuzzy numbers, including those, which are inputs and/or outputs of the F-Calc system. F-Ranking includes six ranking methods: three defuzzification based and three pairwise comparison ones. The structure of F-CalcRank as well as input and output information and the user interfaces of both F-Calc and F-Ranking systems, which can also be used independently, are presented. Examples of computing functions of fuzzy arguments and ranking of fuzzy numbers using implemented methods as well as exploring a real case study in agro-ecology with the use of a math model in fuzzy environment are considered. These examples stress the features and novelty of F-CalcRank system as well as presented applied research. The computer modules created within F-CalcRank are a basis for different FMCDA models developed by the authors. F-CalcRank system is intended for university education, research and various applications in engineering and technology.
