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Found 580 dataset(s) matching "bayesian".
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This U.S. Geological Survey (USGS) data release represents tabular and geospatial data for the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The data...
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In this work we are concerned with the conceptual design of large-scale diagnostic and health management systems that use Bayesian networks. While they are potentially powerful, improperly...
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In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition....
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This U.S. Geological Survey (USGS) data release contains the data used in the USGS Scientific Investigations Report 2018-5053 entitled "An exploratory Bayesian network for estimating the...
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One of NASA’s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there...
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In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to characterizing clique tree...
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Drinking water treatment plants rely on purification of contaminated source waters to provide communities with potable water. One group of possible contaminants are enteric viruses. Measurement...
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In this paper, a probabilistic delamination location and size detection framework is proposed. The delamination probability image using Lamb wave-based damage detection is constructed using the...
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This USGS data release represents tabular and geospatial data for the Gulf Sturgeon Bayesian Network Model. The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast...
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A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef...
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Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to...
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The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation via Particle...
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State-space models offer researchers an objective approach to modeling complex animal location datasets, and state-space model behavior classifications are often assumed to have a link to animal...
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Background Fluctuating asymmetry is assumed to measure individual and population level developmental stability. The latter may in turn show an association with stress, which can be...
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Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
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Supplementary data for "Ring C, Blanchette A, Klaren WD, Fitch S, Haws L, Wheeler MW, DeVito M, Walker N, Wikoff D. A multi-tiered hierarchical Bayesian approach to derive toxic equivalency...
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Python module "optbayesexpt" uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given a parametric model -...
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Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model -...
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The dataset is lake dissolved oxygen concentrations obtained form plots published by Gelda et al. (1996) and lake reaeration model simulated values using Bayesian Monte Carlo methods (Chaudhary...
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Since the publication of the Adverse Outcome Pathway (AOP) for skin sensitization, there have been many efforts to develop systematic approaches to integrate the information generated from...
