2018
DOI: 10.2991/ijcis.11.1.84
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Robustness of general Triple I method for fuzzy soft sets

Abstract: The stability and robustness analysis is a vital issue of fuzzy soft inference. In this paper, λ −Triple I inference methods based on the fuzzy soft modus ponens (FSMP) and fuzzy soft modus tollens (FSMT) are presented. The related computational formulas for inference conclusions with respect to the residual pair are given. Robustness of λ −Triple I inference methods for FSMP and FSMT are analyzed. Finally, robustness analysis of general Triple I inference methods for multiple fuzzy soft rule in the FSMP model… Show more

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Cited by 9 publications
(3 citation statements)
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“…Hence fuzzy logic (Hajek 1998;Wang 2006), probability logic (Adams 1998), rough logic (Pawlak 1991), quantitative logic (Wang 2009), attribute logic (Ganter et al 1999;) and other non-classical logic (Wang 2006) are widely studied. In the study of fuzzy reasoning, Wang (1999) improved the CRI method of fuzzy reasoning and proposed the full implication triple I method of fuzzy reasoning, which has been developed by many researchers, e.g., Song (2000), Qin (2017), Wang (2018) and others.…”
Section: Introductionmentioning
confidence: 99%
“…Hence fuzzy logic (Hajek 1998;Wang 2006), probability logic (Adams 1998), rough logic (Pawlak 1991), quantitative logic (Wang 2009), attribute logic (Ganter et al 1999;) and other non-classical logic (Wang 2006) are widely studied. In the study of fuzzy reasoning, Wang (1999) improved the CRI method of fuzzy reasoning and proposed the full implication triple I method of fuzzy reasoning, which has been developed by many researchers, e.g., Song (2000), Qin (2017), Wang (2018) and others.…”
Section: Introductionmentioning
confidence: 99%
“…During the past few years, many studies on the relationships among different mathematical models that can be used to handle uncertainty have been done [4,12,22,36]. In addition, various hybrid soft set models have been proposed by combining soft set theory with other models such as fuzzy sets and rough sets [20].…”
Section: Introductionmentioning
confidence: 99%
“…Defects and doping in materials are widely and extensively studied in materials science and nanotechnology . For ferroelectrics, the manipulation of native defects within the material affects properties greatly and can also be used to engineer hysteresis loop features .…”
Section: Introductionmentioning
confidence: 99%