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Autor:
Jiri Mockor
Publikováno v:
FUZZ-IEEE
Functors with objects functions representing fuzzy objects in some categories of sets with similarity relations are defined and relationships between these functors are investigated. For fuzzy objects some closure operators are introduced and continu
Autor:
M. Ehtiawesh, Mahdi Mahfouf
Publikováno v:
FUZZ-IEEE
The Self-Organising Fuzzy Logic Controller (SOFLC) which is a modified and extended version of the traditional Fuzzy logic controller (FLC) was introduced to enable the controller to modify its structure based on its evaluation to the performance of
Publikováno v:
FUZZ-IEEE
Intuitionistic Fuzzy TOPSIS (IFT) is an effective decision making technique for fuzziness nature of linguistic assessments. This paper proposes a novel methodology for Multiple Attribute Group Decision Making (MAGDM) problems in intuitionistic fuzzy
Publikováno v:
FUZZ-IEEE
In 1996, Zadeh coined Computing With Words (CWWs) to be a methodology in which words are used instead of numbers for computing and reasoning. One of the main challenges which faced the CWWs paradigm has been modelling words adequately. Mendel has poi
Autor:
Marta C. Ferreira, Susana M. Vieira, Catia M. Salgado, Hanna Schäfer, Joaquim L. Viegas, Carlos Azevedo, João M. C. Sousa
Publikováno v:
FUZZ-IEEE
This papers proposes two novel approaches for the identification of Takagi-Sugeno fuzzy models with time variant and invariant features. The proposed Mixed Fuzzy Clustering algorithm is proposed for determining the parameters of Takagi-Sugeno fuzzy m
Publikováno v:
FUZZ-IEEE
Ordinary fuzzy sets have been recently extended to intuitionistic and hesitant fuzzy sets, which are frequently used for the solution of decision-making problems. All these extensions aim at better defining the membership values or functions of the c
Publikováno v:
FUZZ-IEEE
In order to overcome the drawbacks of AHP in solving complex decision-making problems, ANP is applied in the evaluation of enterprise technology innovation ability. Due to Interval type-2 fuzzy sets can handle uncertainty of linguistic variables in a
Autor:
Sundaram Suresh, K. Subramanian
Publikováno v:
FUZZ-IEEE
Interval Type-2 fuzzy systems have been shown to be extremely capable of handling vagueness as well as uncertainty in data, while complex-valued fuzzy sets have been demonstrated to be capable of solving classification problems efficiently. This pape
Publikováno v:
FUZZ-IEEE
As an integral part of interval type-2 fuzzy logic system (IT2FLS), type reduction (TR) plays a vital role in determining the performance of IT2FLS. Out of many type reduction algorithms, only Karnik-Mendel type TR algorithms capture the essence of i
Publikováno v:
FUZZ-IEEE
Hesitant fuzzy sets are an extension of ordinary fuzzy sets. They are composed of dual hesitant fuzzy sets, interval valued hesitant fuzzy sets, generalized hesitant fuzzy sets, hesitant fuzzy linguistic term sets, and triangular fuzzy hesitant fuzzy