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Chapter 15
DOI: 10.4018/978-1-5225-0914-1.ch015
ABSTRACT
In the present chapter, we give an overview of computational iterative schemes for fuzzy system of linear
equations. We also consider fully fuzzy linear systems (FFLS) and demonstrate a class of the existing
iterative methods using the splitting approach for calculating the solution. Furthermore, the main aim in
this work is to design a numerical procedure for improving this algorithm. Some numerical experiments
are illustrated to show the applicability of the methods and to show the efciency of proposed algorithm,
we report the numerical results of large-scaled fuzzy problems.
INTRODUCTION
Unfailing real world problems in economics, finance, mechanics etc. can lead to solving a system of
linear equations. There are many methods for solving linear systems, see(Barrett et al., 1994; Edalatpa-
nah, 2008; Eisenstat, Elman, & Schultz, 1983; Greenbaum, 1997; Martins, Trigo, & Evans, 2007; Saad,
2003; Saberi Najafi & Edalatpanad, 2013a; Saberi Najafi & Edalatpanah, 2013b, 2013c, 2014b; Saberi
Najafi & Edalatpanah, 2011; Varga, 2009; Young, 2014; Zhang, Huang, Cheng, & Wang, 2012) and the
references therein. Let us consider the following linear systems
Ax=b, (1)
However, when the estimation of the system coefficients is imprecise and only some vague knowl-
edge about the actual values of the parameters is available, it may be convenient to represent some or
all of them with fuzzy numbers. Fuzzy data is being used as a natural way to describe uncertain data.
Fuzzy concept was introduced by Zadeh (Zadeh, 1965, 1972) and following his work, many papers and
books were published in fuzzy system theory; see (Bellman & Zadeh, 1970; Bezdek, 2013; Chen, 2000;
Cordón, 2001; Driankov, Hellendoorn, & Reinfrank, 2013; Hájek, 1998; Höppner, 1999; Jang & Sun,
Modifed Iterative Methods
for Solving Fully Fuzzy
Linear Systems
S. A. Edalatpanah
Ayandegan Institute of Higher Education, Tonekabon, Iran