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» A new extension of fuzzy sets using rough sets: R-fuzzy sets
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ICAI
2009
13 years 5 months ago
Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach
- There are many applications dealing with incomplete data sets that take different approaches to making imputations for missing values. Most tackle the problem for numerical input...
Pilar Rey del Castillo, Jesus Cardenosa
EUSFLAT
2009
146views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Opposite Fuzzy Sets with Applications in Image Processing
Diverse forms of the concept of opposition are already existent in philosophy, linguistics, psychology and physics. The interplay between entities and opposite entities is apparent...
Hamid R. Tizhoosh
IWPEC
2010
Springer
13 years 5 months ago
Inclusion/Exclusion Branching for Partial Dominating Set and Set Splitting
Abstract. Inclusion/exclusion branching is a way to branch on requirements imposed on problems, in contrast to the classical branching on parts of the solution. The technique turne...
Jesper Nederlof, Johan M. M. van Rooij
GIS
2000
ACM
13 years 7 months ago
Fuzzy set theory and thematic maps: accuracy assessment and area estimation
Traditionally, the classes in thematic maps have been treated as crisp sets, using classical set theory. In this formulation, map classes are assumed to be mutually exclusive and e...
Curtis E. Woodcock, Sucharita Gopal
IFSA
2007
Springer
149views Fuzzy Logic» more  IFSA 2007»
14 years 1 months ago
From Interval Computations to Constraint-Related Set Computations: Towards Faster Estimation of Statistics and ODEs Under Interv
One of the important components of granular computing is interval computations. In interval computations, at each intermediate stage of the computation, we have intervals of possi...
Martine Ceberio, Vladik Kreinovich, Andrzej Pownuk...