2018
DOI: 10.1016/j.asoc.2018.08.025
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Verification of fuzzy UML models with fuzzy Description Logic

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Cited by 8 publications
(7 citation statements)
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“…Table 2 summarizes the data derived from the study of Li et al [ 10 ] with the inclusion of the cumulative uncertainty of results. A linguistic value representing the degrees from completely false (0) to completely true (1) was utilized to interpret the reasoning approach in the fuzzy optimization analysis [ 30 ]. Past studies claimed that the fuzzy constraints of non-linear models might be difficult to run in the mathematical software such as CPLEX and Lingo [ 31 , 32 ].…”
Section: Methodsmentioning
confidence: 99%
“…Table 2 summarizes the data derived from the study of Li et al [ 10 ] with the inclusion of the cumulative uncertainty of results. A linguistic value representing the degrees from completely false (0) to completely true (1) was utilized to interpret the reasoning approach in the fuzzy optimization analysis [ 30 ]. Past studies claimed that the fuzzy constraints of non-linear models might be difficult to run in the mathematical software such as CPLEX and Lingo [ 31 , 32 ].…”
Section: Methodsmentioning
confidence: 99%
“…Moreover, Table 2 shows the data derived from the study of Abdel Aziz and Salama [27] with the additional incorporation of the cumulative uncertainty of results. A linguistic value that applies the true value theory, ranging from completely false (0) to completely true (1), was utilized to estimate the reasoning approach in the fuzzy optimization analysis [40]. Figure 1 illustrates the algorithm flowchart of the fuzzy system in the present work.…”
Section: Methodsmentioning
confidence: 99%
“…However, we did include those works proposing transformations if the representation in the target domain has a specific purpose related to uncertainty analysis, and it is shown in the paper. For instance, we included [117,118], which transform from Fuzzy UML models to Fuzzy Description Logics and to Fuzzy Ontologies, because they use the representation in the target domain for uncertainty analysis purposes. Third, we did not consider works proposing representations of uncertainty that do not use software modeling notations; for example those that use mathematical models [204], programming languages [136], programming libraries [152,173], or use lower-level modeling notations, such as partial Kripke structures [132].…”
Section: Inclusion and Exclusion Criteriamentioning
confidence: 99%
“…For example, a UML Profile (FAME) [44,45] was proposed for adding fuzzy information to UML model elements. However, most of the works on expressing uncertainty using Fuzzy set theory employ Fuzzy UML [58,59,60,91] or Fuzzy Entity-Relationship (ER) models [55,57], sometimes combined with Description logic [26,56,61,117,118,123] or with Fuzzy probabilities [111,112].…”
Section: Types Of Uncertainty Addressedmentioning
confidence: 99%