Results 11 to 20 of about 43,829 (264)
Recent advances in polynomial chaos method for uncertainty propagation
Zhongguo Jianchuan Yanjiu, 2021 Uncertainty exists widely in engineering design. As one of the key components of engineering design, uncertainty propagation and quantification has always been an important research topic.
Fenfen XIONG +4 more
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Remote Sensing, 2023 To improve the confidence and quality of measurements produced by regional and international infrasound monitoring networks, this work investigates a methodology for propagating uncertainty associated with on-site measurement systems.
Séverine Demeyer +4 more
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Tecnura, 2023 Context: The natural spatial and temporal variability (uncertainty) of the inputs involved in hydrodynamic modeling for hazard assessment and delineation of potentially flood-prone areas is propagated in the output variables of the models.
Alfonso Mariano Ramos-Cañón +2 more
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Representative Points Based on Power Exponential Kernel Discrepancy
Axioms, 2022 Representative points (rep-points) are a set of points that are optimally chosen for representing a big original data set or a target distribution in terms of a statistical criterion, such as mean square error and discrepancy.
Zikang Xiong +3 more
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UNCERTAINTY QUANTIFICATION IN FRENETIC CALCULATIONS OF ALFRED LEAD-COOLED FAST REACTOR [PDF]
EPJ Web of Conferences, 2021 The paper shows the application of the most recent sensitivity techniques implemented in Serpent-2 in order to propagate the uncertainty from the nuclear data to the macroscopic, homogenised cross sections of the ALFRED reactor, which is then simulated ...
Abrate Nicolò +2 more
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Input database related uncertainty of Biome-BGCMuSo agro-environmental model outputs
International Journal of Digital Earth, 2021 Gridded model assessments require at least one climatic and one soil database for carrying out the simulations. There are several parallel soil and climate database development projects that provide sufficient, albeit considerably different, observation ...
Nándor Fodor +12 more
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Uncertainty Propagation in Node Classification
2022 IEEE International Conference on Data Mining (ICDM), 2022 Quantifying predictive uncertainty of neural networks has recently attracted increasing attention. In this work, we focus on measuring uncertainty of graph neural networks (GNNs) for the task of node classification. Most existing GNNs model message passing among nodes. The messages are often deterministic.
Xu, Zhao +3 more
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Buildings, 2022 Air-based BIPV/T is of significant research interest in reducing energy load and improving indoor comfort. As many factors related to meteorology, geometry and operation contribute to the thermal performance of BIPV/T, especially for one kind of hybrid ...
Juanli Guo +3 more
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Uncertainty propagation or box propagation
Mathematical and Computer Modelling, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Roberto Barrio +3 more
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Tropospheric links to uncertainty in stratospheric subseasonal predictions [PDF]
Atmospheric Chemistry and PhysicsVariability in the stratosphere, especially extreme events such as sudden stratospheric warmings (SSWs), can impact surface weather. Understanding stratospheric prediction uncertainty is therefore crucial for skillful surface weather forecasts on weekly
R. W.-Y. Wu +5 more
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