Fuzzy system F-CalcRank for calculating functions of fuzzy arguments and ranking of fuzzy numbers

2021 ◽  
pp. 1-16
Author(s):  
Alexander Radaev ◽  
Alexander Korobov ◽  
Boris Yatsalo
Keyword(s):  
User Interfaces ◽  
Fuzzy System ◽  
Fuzzy Numbers ◽  
University Education ◽  
Fuzzy Arithmetic ◽  
Membership Functions ◽  
Ranking Methods ◽  
Fuzzy Environment ◽  
System F ◽  
Ranking Of Fuzzy Numbers

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.

Fuzzy Reliability of an Imprecise Failure to Start of an Automobile Using Pseudo-Parabolic Fuzzy Numbers

2018 ◽  
Vol 14 (03) ◽  
pp. 323-341 ◽  
Author(s):  
F. Abbasi
Keyword(s):  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Extension Principle ◽  
Fuzzy Arithmetic ◽  
Fuzzy Reliability ◽  
Fuzzy Environment ◽  
Distributed Components ◽  
Proposed Model ◽  
New Type ◽  
The Membership Function

In this paper, we propose the notion of pseudo-parabolic fuzzy numbers and the component failure probabilities are considered as a new type of fuzzy number as pseudo-parabolic to incorporate the uncertainties in the parameter, due to a more realistic estimate of them. Then, we analyze the reliability of fuzzy system (particularly, series and parallel system) with independent and non-identically distributed components, and using the new operations of TA [F. Abbasi et al., Journal of Intelligent and Fuzzy Systems 29 (2015) 851–861], due to the smaller results support, easier calculations and special properties than fuzzy arithmetic operations based on the extension principle (in the domain of the membership function) and the interval arithmetic (in the domain of the [Formula: see text]-cuts). We provide a more realistic fuzzy reliability analysis. Finally, an imprecise failure to start of an automobile is considered in fuzzy environment. The reliability of components of the proposed model is considered as pseudo-parabolic fuzzy numbers.

scholarly journals Fuzzy Number Addition with the Application of Horizontal Membership Functions

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Andrzej Piegat ◽  
Marcin Pluciński
Keyword(s):  
Interval Arithmetic ◽  
Fuzzy Numbers ◽  
Order Relation ◽  
Extension Principle ◽  
Fuzzy Arithmetic ◽  
Multidimensional Approach ◽  
Membership Functions ◽  
Multidimensional Information ◽  
Rdm Arithmetic ◽  
Horizontal Membership Functions

The paper presents addition of fuzzy numbers realised with the application of the multidimensional RDM arithmetic and horizontal membership functions (MFs). Fuzzy arithmetic (FA) is a very difficult task because operations should be performed here on multidimensional information granules. Instead, a lot of FA methods useα-cuts in connection with 1-dimensional classical interval arithmetic that operates not on multidimensional granules but on 1-dimensional intervals. Such approach causes difficulties in calculations and is a reason for arithmetical paradoxes. The multidimensional approach allows for removing drawbacks and weaknesses of FA. It is possible thanks to the application of horizontal membership functions which considerably facilitate calculations because now uncertain values can be inserted directly into equations without using the extension principle. The paper shows how the addition operation can be realised on independent fuzzy numbers and on partly or fully dependent fuzzy numbers with taking into account the order relation and how to solve equations, which can be a difficult task for 1-dimensional FAs.

scholarly journals On a Flow-Shop Scheduling Problem with Fuzzy Pentagonal Processing Time

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Majed G. Alharbi ◽  
Hamiden Abd El-Wahed Khalifa
Keyword(s):  
Processing Time ◽  
Fuzzy Numbers ◽  
Flow Shop ◽  
Simple Approach ◽  
Flow Shop Scheduling ◽  
Fuzzy Arithmetic ◽  
Scheduling Problem ◽  
Numerical Illustration ◽  
Fuzzy Environment ◽  
Ranking Technique

Scheduling involves planning and arranging jobs across a coordinated set of events to satisfy the customer’s demands. In this article, we present a simple approach for the flow-shop (FS) scheduling problem under fuzzy environment in which processing time of jobs are represented by pentagonal fuzzy numbers. This study is intended to reduce the rental cost of the machine in compliance with the rental policy. The fuzzy FS scheduling problem is solved without converting the processing time into its equivalent crisp numbers using a robust ranking technique and a fuzzy arithmetic pentagonal fuzzy numbers. A numerical illustration indicates that the approach is workable, accurate, and relevant.

Tribomaterial Evaluation and Ranking Using Fuzzy Multicriteria Decision Making

2006 ◽  
Author(s):  
M. F. Wani
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Multicriteria Decision Making ◽  
Fuzzy Arithmetic ◽  
Membership Functions ◽  
Multicriteria Decision ◽  
Fuzzy Membership Functions ◽  
Step Procedure ◽  
Criteria For Evaluation ◽  
Ranking Index

A procedure based on fuzzy multicriteria decision making is developed for evaluation and ranking of tribomaterials. Tribomaterial properties which influence performance of triboelements at operational stage are considered as criteria for evaluation of tribomaterial. Tribomaterial properties, weighting factors and desired values are converted into fuzzy membership functions called trapezoidal fuzzy numbers. Tribomaterial ranking index is evaluated from weighted fuzzy tribomaterial suitability value for various degrees of optimism through a series of fuzzy arithmetic operations. Higher the value of index better is ranking of tribomaterial. A step by step procedure for evaluation and ranking of tribomaterial is suggested. An example of plain bearing has been presented for illustration of the procedure.

Estimation of Failure Using Fault Tree Analysis Based on New Operations on LR-Type Flat Fuzzy Numbers

2020 ◽  
pp. 1-22
Author(s):  
F. Abbasi ◽  
T. Allahviranloo
Keyword(s):  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Fault Tree Analysis ◽  
Extension Principle ◽  
Fuzzy Arithmetic ◽  
General Shape ◽  
Fuzzy Environment ◽  
Distributed Components ◽  
Proposed Model ◽  
Arithmetic Operator

In this paper, we analyze the reliability of fuzzy system (particularly, series and parallel system) with independent and non-identically distributed components using the new operations of TA [F. Abbasi, T. Allahviranloo and S. Abbasbandy, A new attitude coupled with fuzzy thinking to fuzzy rings and fields, Journal of Intelligent and Fuzzy Systems 29 (2015) 851–861.] due to the smaller results support, easier calculations and special properties than operations based on the extension principle (in the domain of the membership function) and the interval arithmetic (in the domain of the [Formula: see text]-cuts). we propose the new fuzzy arithmetic operations based on transmission average(TA) on LR type flat fuzzy numbers. In the proposed formulae, LR type flat fuzzy numbers are not restricted to have the same [Formula: see text] and [Formula: see text] shape functions. This allows arithmetic operator for arithmetic involving LR type flat fuzzy numbers of different and general shape. Finally, an imprecise failure to start of an automobile is considered in fuzzy environment. The reliability of components of the proposed model is considered as LR type flat fuzzy numbers.

Intuitionistic Fuzzy Measures of Correlation Coefficient of Intuitionistic Fuzzy Numbers Under Weakest Triangular Norm

2019 ◽  
Vol 8 (1) ◽  
pp. 48-64 ◽  
Author(s):  
Mohit Kumar
Keyword(s):  
Correlation Coefficient ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Fuzzy Arithmetic ◽  
Triangular Norm ◽  
Arithmetic Operations ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Technology Level

The correlation coefficient of variables has wide applications in statistics and is often calculated in crisp or fuzzy environment. This article extends the application of correlation coefficient to intuitionistic fuzzy environment. In this article, a new method is proposed to measure the correlation coefficient of intuitionistic fuzzy numbers using weakest triangular norm based intuitionistic fuzzy arithmetic operations. Different from previous studies, the correlation coefficient computed in this article is an intuitionistic fuzzy number rather than a crisp or fuzzy number. It is well known that the weakest t-norm arithmetic operations effectively reduce fuzzy spreads (fuzzy intervals) and provide more exact results. Therefore, a simplified, effective and exact method based on weakest t-norm arithmetic operations is presented to compute the correlation coefficient of intuitionistic fuzzy numbers. To illustrate the proposed method, the correlation coefficient between the technology level and management achievement from a sample of 15 machinery firms in Taiwan is calculated using proposed approach.

scholarly journals A computational method for fuzzy arithmetic operations

1970 ◽  
Vol 4 (1) ◽  
pp. 18-22 ◽  
Author(s):  
Thowhida Akther ◽  
Sanwar Uddin Ahmad
Keyword(s):  
Membership Function ◽  
Interval Arithmetic ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Computational Method ◽  
Fuzzy Arithmetic ◽  
Membership Functions ◽  
Computer Implementation ◽  
Arithmetic Operations ◽  
International University

In this paper, a computer implementation to evaluate the arithmetic operations on two fuzzy numbers with linear membership functions has been developed. The fuzzy arithmetic approached by the interval arithmetic is used here. The algorithm of the developed method with a numerical example is also provided. Using this method four basic arithmetic operations between any two TFNs can be evaluated without complexity. Keywords: Fuzzy arithmetic, Fuzzy number, Membership Function, Interval arithmetic, α - cut. DOI: 10.3329/diujst.v4i1.4350 Daffodil International University Journal of Science and Technology Vol.4(1) 2009 pp.18-22

scholarly journals Reinstatement of the Extension Principle in Approaching Mathematical Programming with Fuzzy Numbers

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1272
Author(s):  
Bogdana Stanojević ◽  
Milan Stanojević ◽  
Sorin Nădăban
Keyword(s):  
Mathematical Programming ◽  
Fuzzy Numbers ◽  
Optimization Problems ◽  
Fuzzy Optimization ◽  
Extension Principle ◽  
Fuzzy Arithmetic ◽  
Advantages And Disadvantages ◽  
Fuzzy Environment ◽  
Basic Ideas ◽  
Mathematical Programming Problems

Optimization problems in the fuzzy environment are widely studied in the literature. We restrict our attention to mathematical programming problems with coefficients and/or decision variables expressed by fuzzy numbers. Since the review of the recent literature on mathematical programming in the fuzzy environment shows that the extension principle is widely present through the fuzzy arithmetic but much less involved in the foundations of the solution concepts, we believe that efforts to rehabilitate the idea of following the extension principle when deriving relevant fuzzy descriptions to optimal solutions are highly needed. This paper identifies the current position and role of the extension principle in solving mathematical programming problems that involve fuzzy numbers in their models, highlighting the indispensability of the extension principle in approaching this class of problems. After presenting the basic ideas in fuzzy optimization, underlying the advantages and disadvantages of different solution approaches, we review the main methodologies yielding solutions that elude the extension principle, and then compare them to those that follow it. We also suggest research directions focusing on using the extension principle in all stages of the optimization process.

A Greedy Algorithm for Fuzzy Shortest Path Problem using Quasi-Gaussian Fuzzy Weights

2013 ◽  
Vol 3 (2) ◽  
pp. 55-70 ◽  
Author(s):  
Madhushi Verma ◽  
K. K. Shukla
Keyword(s):  
Greedy Algorithm ◽  
Shortest Path ◽  
Fuzzy Numbers ◽  
Shortest Path Problem ◽  
Fuzzy Arithmetic ◽  
Membership Functions ◽  
Packet Arrival ◽  
Gradient Based ◽  
Fuzzy Weights ◽  
First Time

Several algorithms exist to determine the shortest path in a network for the crisp case where the weights are real numbers. In the real world, these weights represent parameters like cost, packet arrival time, link capacity etc which are not naturally precise. To model the uncertainty involved, for the first time we use the Gaussian fuzzy numbers as weights and a method has been presented in this paper to determine the fuzzy shortest path. Gaussian membership functions are preferred over other membership functions (triangular and trapezoidal) that are easy to analyze because it is continuous and differentiable enabling efficient gradient based optimization and it is simpler to represent because it requires fewer parameters. The issue of performing fuzzy arithmetic operations to calculate the fuzzy shortest path length and the corresponding fuzzy shortest path in the network has been addressed and to tackle it the concept of decomposed fuzzy numbers has been used. Also, a greedy algorithm which is an extension of Dijkstra’s algorithm for fuzzy shortest path problem has been proposed.

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