A review on classification methods for solving fully fuzzy linear systems

Fully Fuzzy Linear System (FFLS) exists when there are fuzzy numbers on both sides of the linear systems. This system is quite significant today since most of the linear systems play with uncertainties of parameters especially in mathematics, engineering and finance. Many researchers and practitione...

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Bibliographic Details
Published inAIP conference proceedings Vol. 1691; no. 1
Format Conference Proceeding
LanguageEnglish
Published Melville American Institute of Physics 11.12.2015
Subjects
Fuzzy systems
Identification methods
Linear systems
Mathematical models
Methods
Numerical methods
Parameter uncertainty
Researchers
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Summary:Fully Fuzzy Linear System (FFLS) exists when there are fuzzy numbers on both sides of the linear systems. This system is quite significant today since most of the linear systems play with uncertainties of parameters especially in mathematics, engineering and finance. Many researchers and practitioners used the FFLS to model their problem and they apply various methods to solve it. In this paper, we present the outcome of a comprehensive review that we have done on various methods used for solving the FFLS. We classify our findings based on parameters’ type used for the FFLS either restricted or unrestricted. We also discuss some of the methods by illustrating numerical examples and identify the differences between the methods. Ultimately, we summarize all findings in a table. We hope this study will encourage researchers to appreciate the use of this method and with that it will be easier for them to choose the right method or to propose any new method for solving the FFLS.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4937055