Fuzzy neighborhood Rough Set
A fuzzy neighborhood rough set method for anomaly detection in large scale data
... using rough set methods requires the transformation ofcontinuous value attributes to discrete intervals, in order to form a grid structure and then form clusters from the cells in the grid ...real ...
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An Exponential Kernel based Fuzzy Rough Sets Model for Feature Selection
... sub set of features for classification with kernel parameter values (θ) are in the interval ...feature set {24,4} are the best features and it ranks first and second for wdbc dataset in all the methods and ...
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Covering-Based Grade Rough Fuzzy Set Models
... covering rough set models and the overlapping information between the set and the equivalence classed proposed in this paper, four kinds of covering grade rough fuzzy set models ...
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Comparison of Robust Nearest Neighbour fuzzy Rough Classifier (RNN-FRC) with KNN and NEC Classifiers
... It was shown that both R d S i (x) or R d T i (x) depends on the nearest miss of x, i.e., the nearest sample from different classes of x. As we know, the statistics of minimum and maximum are very sensitive to noisy ...
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A note on inequalities and critical values of fuzzy rough variables
... objects, rough set theory was initialized by Pawlak [] in , which provides a new powerful mathematical ap- proach to handling imperfect knowledge in the real ...a set by other sets. Thus a ...
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Multigranulation Decision theoretic Rough Set Based on Incomplete Interval valued Information Systems
... Pawlak rough set theory[1] is a powerful mathematical tool for uncertainty management, especially in describing the uncertainty of the ...data. Rough set theory has been widely used in many ...
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A characterization of Fuzzy neighborhood commutative division rings
... We give a characterization of fuzzy neighborhood commutative division ring; and present an alternative formulation of boundedness introduced in fuzzy neighborhood rings.. The notion of B[r] ...
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A New Approach to Rough Lattices and Rough Fuzzy Lattices Based on Fuzzy Ideals
... I T is well known that, in the real world, classical methods are not always successful in dealing with the problems in economy, engineering and social science, because of various types of uncertainties presented in these ...
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On Multigranular Rough Soft Set
... system. Rough set theory plays a vital role to solve imprecise ...multigranular rough set is an efficient tool to work on multivalued information ...Soft set theory is also deal ...
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Granular computing with multiple granular layers for brain big data processing
... The rough set theory developed by Pawlak in 1982 is an effective model to acquire knowledge in information sys- tem with upper approximation and lower approximation as its core concepts, making decisions ...
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A Study on Rough, Fuzzy and Rough Fuzzy Bi-ideals of Ternary Semigroups
... of fuzzy sets was introduced by Zadeh [23]. Fuzzy set theory is a generalization of set ...the fuzzy set theory have been found in various ...of rough sets was introduced ...
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Vol 8, No 12 (2017)
... the Fuzzy set theory and the Rough set ...of Fuzzy sets and Rough sets are powerful mathematical tools for modeling various types of ...uncertainties. Fuzzy set ...
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ROUGH BIPOLAR NEUTROSOPHIC SET
... neutrosophic set theory and rough neutrosophic set theory are emerging as powerful tool for dealing with uncertainty, and indeterminate, incomlete, and inprecise ...neutrsophic set”. In the ...
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Retrieving the Missing Information from Information Systems Using Rough Set, Covering Based Rough Set and Soft Set
... soft set proposed, by Molodtsov in 1999, is a new method for handling uncertain data[4, ...5].Soft set are called either binary or basic or elementary neighborhood systems ...soft set is a ...
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Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
... In rough categorical clustering, mainly the data set is expressed as the decision table by introducing a decision ...data set aiming to find a cluster which best represents the data according to some ...
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A rough set based solar powered flood water purification system with a Fuzzy Logic model
... utilize fuzzy logic and rough set theory to make sure the water is clean and is safe for ...the fuzzy controller treatment and pump speed ...purification. Rough Set theory was ...
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Breast Tissue Classification via Interval Type 2 Fuzzy Logic Based Rough Set
... type-2 fuzzy logic as classifier, an automatically generated rules will be applied to the ...type-2 fuzzy logic using Mamdani ...using rough set ...on rough set rules obtains 89% ...
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EEG Signal Classification Using Fuzzy-Rough Nearest Neighbours (FRNN) Model For Person Authentication
... as fuzzy set theory and rough set theory are needed to classify the ...of fuzzy set theory, rough set theory and KNN called Fuzzy-Rough Nearest ...
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Neighborhood and Efficient Triple Connected Domination Number of a Fuzzy Graph
... nontrivial fuzzy graph G is said to be a Neighborhood triple Connected dominatingset, if S is a dominating set and the induced sub graph < N(S) > is a triple ...all Neighborhood triple ...
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Association Rule Granulation using Rough Sets on Intuitionistic Fuzzy Approximation Spaces and Granular Computing
... of rough sets [Paw91, PS07a, PS07b, PS07c] introduced by ...to rough set the information granulation is due to indiscernibility of objects caused by lack of information about ...
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