Results 61 to 70 of about 185,811 (251)
Rough fuzzy model based feature discretization in intelligent data preprocess
Journal of Cloud Computing: Advances, Systems and Applications, 2021 Feature discretization is an important preprocessing technology for massive data in industrial control. It improves the efficiency of edge-cloud computing by transforming continuous features into discrete ones, so as to meet the requirements of high ...
Qiong Chen, Mengxing Huang
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Rough set based gas turbine fault isolation study [PDF]
, 2010 Gas path fault isolation is one of the key techniques in Engine Health Management systems. In order to accomplish gas path fault isolation successfully for a gas turbine engine, both an accurate off-design performance model and an effective fault ...
Wang, Lihui.
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Fuzzy rough positive region based nearest neighbour classification
, 2012 This paper proposes a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some shortcomings and we overcome ...
Verbiest, Nele +7 more
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Information veins and re-sampling with rough set theory
, 2008 Rough Set Theory (RST), since its introduction in Pawlak (1982), continues to develop as an effective tool in data mining. Within a set theoretical structure, its remit is closely concerned with the classification of objects to decision attribute values,
Benjamin Griffiths, Griffiths, Benjamin
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ISPRS International Journal of Geo-Information, 2020 Generalization of geographic information enables cognition and understanding not only of objects and phenomena located in space but also the relations and processes between them.
Anna Fiedukowicz
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Neutrosophic Rough Soft Set – A Decision Making Approach to Appendicitis Problem [PDF]
Neutrosophic Sets and Systems, 2017 Classification based on fuzzy logic techniques can handle uncertainty to a certain extent as it provides only the fuzzy membership of an element in a set.
Kanika Bhutani, Swati Aggarwal
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IEEE Access, 2020 Recently, the concept of a fuzzy $\alpha $ - neighborhood operator with reflexivity was established and a fuzzy rough set covering based on a fuzzy $\alpha $ - neighborhood operator was defined by Zhang et al. As a generalization of Zhang et al. models,
Jue Ma +4 more
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Rough sets based on fuzzy ideals in distributive lattices
Open Mathematics, 2020 In this paper, we present a rough set model based on fuzzy ideals of distributive lattices. In fact, we consider a distributive lattice as a universal set and we apply the concept of a fuzzy ideal for definitions of the lower and upper approximations in ...
Yang Yongwei, Zhu Kuanyun, Xin Xiaolong
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On the lattice of fuzzy rough sets
Fuzzy Sets and SystemsBy the means of lower and upper fuzzy approximations we define quasiorders. Their properties are used to prove our main results. First, we characterize those pairs of fuzzy sets which form fuzzy rough sets w.r.t. a t-similarity relation $θ$ on $U$, for certain t-norms and implicators.
Dávid Gégény, Sándor Radeleczki
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Study on Interval-valued Dual Hesitant Fuzzy β Covering Rough Set Model
Journal of Harbin University of Science and TechnologyTo effectively handle the problem of decision-making with interval-valued hesitant fuzzy information, this paper proposes four models of interval-valued dual hesitant fuzzy β coverage rough sets,which are combined with interval-valued dual hesitant fuzzy
REN Haowei, WANG Qinghai
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