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Titlebook: Aggregation and Fusion of Imperfect Information; Bernadette Bouchon-Meunier Book 1998 Springer-Verlag Berlin Heidelberg 1998 Unvollst?ndig

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發(fā)表于 2025-3-23 12:31:34 | 只看該作者
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發(fā)表于 2025-3-24 05:17:36 | 只看該作者
Book 1998 of data provided by several sources. It focuses on the case where the availability knowledge is imperfect, which means that uncertainty and/or imprecision must be taken into account. The book contains both theoretical and applied studies of aggregation and fusion methods in the main frameworks: pro
16#
發(fā)表于 2025-3-24 08:29:46 | 只看該作者
1434-9922 ence theory, fuzzy set and possibility theory. The latter is more developed because it allows to manage both imprecise and uncertain knowledge. Applications to decision-making, image processing, control and classification are described.978-3-662-11073-7978-3-7908-1889-5Series ISSN 1434-9922 Series E-ISSN 1860-0808
17#
發(fā)表于 2025-3-24 12:45:34 | 只看該作者
Erica H. Dunn,David J. T. Husselle integrated rigorously into a target tracking process, to reflect the origin of the localization measurements better. In all cases, the solutions found are placed in relation to those of the main competitive approaches currently used.
18#
發(fā)表于 2025-3-24 18:50:12 | 只看該作者
Scott H. Stoleson,Steven R. Beissingermetric aggregation operators are proposed to apply asymmetric similarity data. The asymmetric operators are defined by using generator function of T-norms. The validity of this model is shown by investigating the characteristic feature of the model and numerical applications.
19#
發(fā)表于 2025-3-24 20:59:17 | 只看該作者
Uncertain Data Aggregation in Classification and Tracking Processese integrated rigorously into a target tracking process, to reflect the origin of the localization measurements better. In all cases, the solutions found are placed in relation to those of the main competitive approaches currently used.
20#
發(fā)表于 2025-3-25 00:44:10 | 只看該作者
A Generalized Fuzzy Clustering Model Based on Aggregation Operators and its Applicationsmetric aggregation operators are proposed to apply asymmetric similarity data. The asymmetric operators are defined by using generator function of T-norms. The validity of this model is shown by investigating the characteristic feature of the model and numerical applications.
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