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Titlebook: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundati; 17th International C Jesús Medina,Man

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IF-CLARANS: Intuitionistic Fuzzy Algorithm for Big Data Clusteringation on real data sets shows that the proposed algorithm can obtain satisfactory clustering results and outperforms other current methods. The clusters quality was evaluated by three well-known metrics.
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Semi-supervised Fuzzy c-Means Variants: A Study on Noisy Label Supervisionarison between existing algorithms, formal improvements have been proposed to guarantee and fasten their convergence. Experiments conducted on real and synthetical datasets under uncertain labels and noise in the constraints show the effectiveness of using fuzzy clustering algorithm for noisy semi-supervised clustering.
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1865-0929 ent of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018..The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators,
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A Fuzzy Close Algorithm for Mining Fuzzy Association Rules a fuzzy adaptation of the well-known Close algorithm which relies on the closure of itemsets. The Close-algorithm needs less passes over the dataset and is suitable when variables are correlated. The algorithm is then compared to other on public datasets.
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Enhanced F-transform Exemplar Based Image Inpaintingd patches and the task of inpainting becomes the task of searching for the most suitable patch from the undamaged part of the image to replace the partially damaged one. Our novelty is in processing based on fuzzy mathematics and new filling order prioritization function.
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A Novel Approach to the Discrete Fuzzy Transform of Higher Degreer degree fuzzy transform and how convenient the latter is computed by the novel approach. Finally, we illustrate and compare the proposed technique with the original discrete fuzzy transform of higher degree.
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