An Interval Approach to Fuzzistics for Interval Type-2 Fuzzy Sets

Liu, Feilong; Mendel, Jerry M.

doi:10.1109/fuzzy.2007.4295508

Cited by 43 publications

(49 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [15] methodology for obtaining the UMF and the LMF of an FOU through the representation theorem proposed by [14] is defined.…”

Section: Type-2 Fuzzy Setsmentioning

confidence: 99%

“…-Rate of correctness: The rate of correctness of the problem is calculated through the equation 15: (15) where RC refers to the correctly answered steps n a problem, PR refers to the number of steps in which the tutoring system decomposed the problem for each student. -Speed Factor: The speed to solve a problem is defined by Eq.…”

Section: Transformationmentioning

confidence: 99%

“…The UMF and the LMF are type-1 membership functions. To obtain the LMF is necessary to calculate its height and its center according to the equations defined by [15] (see Eqs. 11 and 12).…”

Section: Definition Of the Umf And The Lmf Of The It2fsmentioning

confidence: 99%

“…The prototypes associated with fuzzy prototypes embedded in the IT2FS are aggregated in order to get only one that represent them. The methodology defined by [15] is used to establish the type-1 fuzzy prototypes embedded within the IT2FS. Table 8 and Fig.…”

Section: Fuzzy Representation Of Prototypesmentioning

confidence: 99%

“…The Representation Theorem (RT) is used to represent and manipulate the overlap of the prototypes to the IT2FS. The following steps, based on the methodology defined by [15], are used to obtain the UMF and the LMF of the IT2FS for representing the fuzzy prototypes: …”

Section: Definition Of the Umf And The Lmf Of The It2fsmentioning

confidence: 99%

See 4 more Smart Citations

An Extension of Fuzzy Deformable Prototypes for predicting student performance on Web-based Tutoring Systems

Vázquez¹,

Romero

Ruiz-Vanoye³

et al. 2015

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

This paper presents an extension of Fuzzy Deformable Prototypes (FDPs) based on the use of interval type-2 fuzzy sets. The aim is to improve FDPs' capabilities for managing uncertainty and imprecision. This extension is applied to predict the academic performance of the students who make use of Web-based tutoring systems. The prediction model contains patterns of behavior that are used to determine the future academic performance of new students based on their affinity with the prototypes previously discovered. Interval Type 2 Fuzzy Sets (IT2FS) were used to handle the imprecision of the academic data caused by the overlapping between the fuzzy representations of prototypes.

show abstract

“…In [15] methodology for obtaining the UMF and the LMF of an FOU through the representation theorem proposed by [14] is defined.…”

Section: Type-2 Fuzzy Setsmentioning

confidence: 99%

Section: Transformationmentioning

confidence: 99%

“…The UMF and the LMF are type-1 membership functions. To obtain the LMF is necessary to calculate its height and its center according to the equations defined by [15] (see Eqs. 11 and 12).…”

Section: Definition Of the Umf And The Lmf Of The It2fsmentioning

confidence: 99%

Section: Fuzzy Representation Of Prototypesmentioning

confidence: 99%

Section: Definition Of the Umf And The Lmf Of The It2fsmentioning

confidence: 99%

See 3 more Smart Citations