Results 61 to 70 of about 439,127 (183)
Integrating heterogeneous knowledges for understanding biological behaviors: a probabilistic approach [PDF]
, 2007 Despite recent molecular technique improvements, biological knowledge remains incomplete. Reasoning on living systems hence implies to integrate heterogeneous and partial informations.
Bourdon, Jérémie +3 more
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Probabilistic Modeling of Updating Epistemic Uncertainty in Pile Capacity Prediction with a Single Failure Test Result [PDF]
, 2017 The model error N has been introduced to denote the discrepancy between measured and predicted capacity of pile foundation. This model error is recognized as epistemic uncertainty in pile capacity prediction. The statistics of N have been evaluated based
Sidi, I. D. (Indra)
core
On certain functionals of normal processes Technical report no. 1 [PDF]
Probabilistic modeling and stochastic process investigations to provide measures of quality of performance and reliability for systems engineering - Chebyshev ...
Cryer, J. D., Leadbetter, M. R.
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BuildingsStructural health monitoring commonly uses natural frequency analysis to assess structural conditions, but direct frequency shifts are often insensitive to minor damage and susceptible to environmental influences like temperature variations.
Xue-Yang Pei +3 more
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PROBABILISTIC MODELING IN STUDIES OF THE ACCURACY THE MANUFACTURE OF ENGINEERING PRODUCTS
Вестник Дагестанского государственного технического университета: Технические науки, 2016 Methodological aspects of the theory of precision Assembly operations in the manufacture of engineering products. Substantiated the advantage of probabilistic modeling in engineering.
E. Z. Batmanov, R. V. Guseynov
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QuantumSoft Set: A Quantum-Inspired Extension of Soft Sets for Evaluating Multimedia Teaching Effectiveness in College English [PDF]
Neutrosophic Sets and SystemsIn real-world decision-making, information is rarely complete, precise, or static. Traditional soft set extensions including HyperSoft Sets and TreeSoft Sets have improved the capacity of modeling uncertain or hierarchical data.
Sheng'en Li
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IEEE AccessReliability Modeling for Power Systems is a very challenging task due to the high complexity of the interactions among its various components. In this paper, we develop a simple probabilistic method for modeling power system reliability based on the ...
Ayman Faza
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ProceedingsPyrethroid usage has risen due to restrictions on other insecticides, prompting interest in biomonitoring data as exposure indicators [...]
Ana Fernandez-Agudo +6 more
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Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing
Journal of Marine Science and EngineeringShip weather routing is heavily dependent on weather forecasts. However, the predictive nature of meteorological models introduces an unavoidable level of uncertainty which, if not accounted for, can compromise navigational safety, operational efficiency,
Marijana Marjanović +3 more
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Deep Probabilistic Graphical Modeling
, 2020 Probabilistic graphical modeling (PGM) provides a framework for formulating an interpretable generative process of data and expressing uncertainty about unknowns, but it lacks flexibility. Deep learning (DL) is an alternative framework for learning from data that has achieved great empirical success in recent years.
openaire +3 more sources