Results 41 to 50 of about 77,667 (184)
Journal of Applied Mathematics, 2014 In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification.
Huani Qin, Darong Luo
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Fuzzy Entropy-assisted Fuzzy-Rough Feature Selection [PDF]
2006 IEEE International Conference on Fuzzy Systems, 2006 Feature selection (FS) is a dimensionality reduction technique that aims to select a subset of the original features of a dataset which offer the most useful information. The benefits of feature selection include improved data visualisation, transparency, reduction in training and utilisation times and improved prediction performance.
null Neil Mac Parthalain +2 more
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Finding fuzzy-rough reducts with fuzzy entropy [PDF]
2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008 Dataset dimensionality is undoubtedly the single most significant obstacle which exasperates any attempt to apply effective computational intelligence techniques to problem domains. In order to address this problem a technique which reduces dimensionality is employed prior to the application of any classification learning.
Neil Mac Parthalain +2 more
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IEEE Access, 2016 Fuzzy entropy and image thresholding are the most direct and effective methods for image segmentation. This paper, taking fuzzy Kapur's entropy as the optimal objective function, with modified discrete Grey wolf optimizer (GWO) as the tool, uses ...
Linguo Li +5 more
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Different Types of Entropy Measures for Type-2 Fuzzy Sets
AxiomsIn this work, we consider De Luca and Termini’s notion of non-probabilistic entropy, and we extend some entropy-like measures of the degree of fuzziness to type-2 fuzzy sets.
Luis Magdalena +3 more
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Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic
, 2010 In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying.
Hsieh, Ming-Shing
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Time dependence of entanglement entropy on the fuzzy sphere
, 2017 We numerically study the behaviour of entanglement entropy for a free scalar field on the noncommutative ("fuzzy") sphere after a mass quench. It is known that the entanglement entropy before a quench violates the usual area law due to the non-local ...
Sabella-Garnier, Philippe
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Semantic Information G Theory and Logical Bayesian Inference for Machine Learning [PDF]
, 2019 An important problem with machine learning is that when label number n\u3e2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where ...
Lu, Chenguang
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Deterministic Annealing Approach to Fuzzy C-Means Clustering Based on Entropy Maximization
Advances in Fuzzy Systems, 2011 This paper is dealing with the fuzzy clustering method which combines the deterministic annealing (DA) approach with an entropy, especially the Shannon entropy and the Tsallis entropy.
Makoto Yasuda
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Conditional Probabilities and Fuzzy Entropy
Journal of Japan Society for Fuzzy Theory and Systems, 1990 Let \((\Omega, S, P)\) be a probability space and \(A \in S\) an event with its indicator function \(1_ A\). It is well-known that the conditional probability with respect to a subfield \(G \subset S\) satisfies \(P(A \mid G) = 1_ A\) if \(A \in G\) and that \(P(A \mid G)\) is a general function on [0,1] if \(A\) is not measurable with respect to \(G\).
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