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The inverse non-stationary problem of identification of defects in an elastic rod [PDF]
INCAS Bulletin, 2021 Non-stationary inverse problems of deformed solid mechanics are among the most underexplored due to, inter alia, increasing dimension of non-stationary problems per unit as compared with stationary and static problems, as well as necessity to consider ...
Grigory V. FEDOTENKOV +3 more
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Two variants of M split estimation – similarities and differences [PDF]
Advances in Geodesy and Geoinformation, 2022 M split estimation is a novel method developed to process observation sets that include two (or more) observation aggregations. The main objective of the method is to estimate the location parameters of each aggregation without any preliminary assumption
Patrycja Wyszkowska, Robert Duchnowski
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Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining
Energies, 2021 Land subsidence caused by groundwater withdrawal induced by mining is a relatively unknown phenomenon. This is primarily due to the small scale of such movements compared to the land subsidence caused by deposit extraction. Nonetheless, the environmental
Artur Guzy, Wojciech T. Witkowski
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Določitev primernega geodetskega datuma z uporabo robustnih statističnih metod ( = Definition of appropriate geodetic datum using robust statistical methods) [PDF]
Geodetski Vestnik, 2016 The correct determination of geodetic datum is an obligatory condition for the proper determination of the point displacements. There are various methods of deformation analysis focused on the right identification of stable points, which ...
Aleš Marjetič, Klemen Kregar
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Point Cloud Denoising Algorithm via Geometric Metrics on the Statistical Manifold
Applied Sciences, 2023 A denoising algorithm was proposed for point cloud with high-density noise. The algorithm utilized geometric metrics on the statistical manifold and applied the idea of clustering K-means based on local statistical characteristics between noise and valid
Xiaomin Duan, Li Feng, Xinyu Zhao
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Robust Aggregation for Federated Learning by Minimum γ-Divergence Estimation
Entropy, 2022 Federated learning is a framework for multiple devices or institutions, called local clients, to collaboratively train a global model without sharing their data.
Cen-Jhih Li +4 more
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Optimal Control for a Nonlocal Model of Non-Newtonian Fluid Flows
Mathematics, 2021 This paper deals with an optimal control problem for a nonlocal model of the steady-state flow of a differential type fluid of complexity 2 with variable viscosity. We assume that the fluid occupies a bounded three-dimensional (or two-dimensional) domain
Evgenii S. Baranovskii +1 more
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Journal of Multivariate Analysis, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pires, Ana M., Branco, João A.
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Robust Estimations for the Tail Index of Weibull-Type Distribution
Risks, 2018 Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination.
Chengping Gong, Chengxiu Ling
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Zhongguo Jianchuan Yanjiu, 2021 ObjectivesIn order to reduce the weight while maintaining the performance of the antenna cover of a deeply submerged body, a parallel variable-fidelity lower confidence bound (PVF-LCB) approach is proposed to optimize the structure of the antenna cover ...
Ji CHENG +6 more
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