scholarly journals Minimal Solution of Complex Fuzzy Linear Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaobin Guo ◽  
Ke Zhang
Keyword(s):  
Linear System ◽  
Linear Equation ◽  
Numerical Procedure ◽  
Minimal Solution ◽  
Sufficient Condition ◽  
Complex Matrix ◽  
Fuzzy Linear System ◽  
Fuzzy Solution ◽  
Fuzzy Linear Systems ◽  
Fuzzy Vector

This paper investigates the complex fuzzy linear equation Cz~=w~ in which C is a crisp complex matrix and w~ is an arbitrary LR complex fuzzy vector. The complex fuzzy linear system is converted to equivalent high order fuzzy linear system Gx~=b~. A new numerical procedure for calculating the complex fuzzy solution is designed and a sufficient condition for the existence of strong complex fuzzy solution is derived in detail. Some examples are given to illustrate the proposed method.

scholarly journals A note on “The nearest symmetric fuzzy solution for a symmetric fuzzy linear system”

2015 ◽  
Vol 23 (2) ◽  
pp. 173-177 ◽  
Author(s):  
Ghassan Malkawi ◽  
Nazihah Ahmad ◽  
Haslinda Ibrahim
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Approximate Solutions ◽  
Fuzzy Linear System ◽  
Fuzzy Solution ◽  
Fuzzy Linear Systems

Abstract This paper provides accurate approximate solutions for the symmetric fuzzy linear systems in (Allahviranloo et al:[1]).

scholarly journals Minimal Solution of Singular LR Fuzzy Linear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
M. Nikuie ◽  
M. Z. Ahmad
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Minimal Solution ◽  
Generalized Inverses ◽  
Drazin Inverse ◽  
Fuzzy Linear System ◽  
Fuzzy Linear Systems

In this paper, the singular LR fuzzy linear system is introduced. Such systems are divided into two parts: singular consistent LR fuzzy linear systems and singular inconsistent LR fuzzy linear systems. The capability of the generalized inverses such as Drazin inverse, pseudoinverse, and {1}-inverse in finding minimal solution of singular consistent LR fuzzy linear systems is investigated.

scholarly journals H-Matrices in Fuzzy Linear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
H. Saberi Najafi ◽  
S. A. Edalatpanah
Keyword(s):  
Linear System ◽  
Theoretical Analysis ◽  
Linear Systems ◽  
Numerical Experiments ◽  
Coefficient Matrix ◽  
System Of Equations ◽  
Linear System Of Equations ◽  
Fuzzy Linear System ◽  
Fuzzy Linear Systems

We consider a class of fuzzy linear system of equations and demonstrate some of the existing challenges. Furthermore, we explain the efficiency of this model when the coefficient matrix is an H-matrix. Numerical experiments are illustrated to show the applicability of the theoretical analysis.

scholarly journals General Solutions of Fully Fuzzy Linear Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
T. Allahviranloo ◽  
S. Salahshour ◽  
M. Homayoun-nejad ◽  
D. Baleanu
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Solution Set ◽  
Solution Sets ◽  
General Solutions ◽  
Fully Fuzzy Linear System ◽  
Fuzzy Linear System ◽  
Fuzzy Linear Systems

We propose a method to approximate the solutions of fully fuzzy linear system (FFLS), the so-calledgeneral solutions. So, we firstly solve the 1-cut position of a system, then some unknown spreads are allocated to each row of an FFLS. Using this methodology, we obtain some general solutions which are placed in the well-known solution sets like Tolerable solution set (TSS) and Controllable solution set (CSS). Finally, we solved two examples in order to demonstrate the ability of the proposed method.

scholarly journals Fully Fuzzy Linear Systems in Python Programming

2020 ◽  
Vol 9 (4) ◽  
pp. 951-956
Keyword(s):  
Linear System ◽  
Fuzzy Number ◽  
Symmetric Matrix ◽  
Triangular Matrix ◽  
New Approach ◽  
Numerical Examples ◽  
Fuzzy Matrix ◽  
Fuzzy Linear System ◽  
Python Programming ◽  
Fuzzy Linear Systems

This paper proposes the python coding for ST decomposition for Triangular, Trapezoidal, and computing the algorithms for the fully fuzzy linear system in python programming. where is a fuzzy matrix, are fuzzy vectors. ST decompose into a product of symmetric matrix (S) and triangular matrix (T) in the form of triangular and trapezoidal fuzzy number matrices. To best illustrate the proposed methods by python coding algorithm with a new approach Python coding has been adopted. Algorithms have been introduced and the numerical examples have been solved by using python techniques. A study of ST decomposition have been done and the solution is obtained with different algorithms. New numerical problems are presented and an example has been solved for this algorithms and the solutions are obtained.

scholarly journals A Novel Weak Fuzzy Solution for Fuzzy Linear System

Entropy ◽  
2016 ◽  
Vol 18 (3) ◽  
pp. 68 ◽  
Author(s):  
Soheil Salahshour ◽  
Ali Ahmadian ◽  
Fudziah Ismail ◽  
Dumitru Baleanu
Keyword(s):  
Linear System ◽  
Fuzzy Linear System ◽  
Fuzzy Solution

scholarly journals The nearest symmetric fuzzy solution for a symmetric fuzzy linear system

2012 ◽  
Vol 20 (1) ◽  
pp. 151-172 ◽  
Author(s):  
T. Allahviranloo ◽  
E. Haghi ◽  
M. Ghanbari
Keyword(s):  
Linear Programming ◽  
Linear System ◽  
Programming Problem ◽  
Fuzzy Number ◽  
Linear Programming Problem ◽  
Vector Solution ◽  
Numerical Examples ◽  
Non Linear Programming ◽  
Fuzzy Linear System ◽  
Fuzzy Solution

Abstract In this paper, the nearest symmetric fuzzy solution for a symmetric L-L fuzzy linear system (S-L-FLS) is obtained by a new metric. To this end, the S-L-FLS is transformed to the non-linear programming problem (NLP). The solution of the obtained NLP is our favorite fuzzy number vector solution. Also, it is shown that if an S-L-FLS has unique fuzzy solution, then its solution is symmetric. Two constructive algorithms are presented in details and the method is illustrated by solving several numerical examples

scholarly journals An Application of Interval Arithmetic for Solving Fully Fuzzy Linear Systems with Trapezoidal Fuzzy Numbers

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Esmaeil Siahlooei ◽  
Seyed Abolfazl Shahzadeh Fazeli
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Interval Arithmetic ◽  
Fuzzy Numbers ◽  
New Method ◽  
Numerical Examples ◽  
Fully Fuzzy Linear System ◽  
Basic Interval ◽  
Fuzzy Linear System ◽  
Fuzzy Linear Systems

We present a method for solving fully fuzzy linear systems using interval aspects of fuzzy numbers. This new method uses a decomposition technique to convert a fully fuzzy linear system into two types of decomposition in the form of interval matrices. It finds the solution of a fully fuzzy linear system by using interval operations. This new method uses interval arithmetic and two new interval operations ⊖ and ⊘. These new operations, which are inverses of basic interval operations + and ×, will be presented in the middle of this paper. Some numerical examples are given to illustrate the ability of proposed methods.

Sign in / Sign up

Export Citation Format

Share Document