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Showing 1 to 9 of 9 for “"Ensemble Prediction"”.

  1. Mesoscale Ensemble Prediction of Mid-Latitude Cyclones

    … assessment of these multiple, distinct mesoscale ensemble subsets, incorporating initial condition, model physics and lateral boundary uncertainties present in mid-latitude cyclone prediction. The use of separate ensemble subsets permitted direct comparison of the contributions from different …

    uiuc Repository record for Mesoscale Ensemble Prediction of Mid-Latitude Cyclones (opens in a new tab)

  2. Improving hydrometeorologic numerical weather prediction forecast value via bias correction and ensemble analysis

    … Columbia, Canada. This research then examined ensemble prediction system design by assessing a three-model suite of multi-resolution limited area mesoscale models. The research employed two different economic models to investigate the ensemble design that produced the highest-quality, most …

    ubc Repository record for Improving hydrometeorologic numerical weather prediction forecast value via bias correction and ensemble analysis (opens in a new tab)

  3. Ensemble forecasting in the Mediterranean sea

    A new methodology is being devised for ensemble ocean forecasting using distributions of the surface wind field derived from a Bayesian Hierarchical Model (BHM). The ocean members are forced with samples from the posterior distribution of the wind during the assimilation of satellite and in-situ …

    bologna Repository record for Ensemble forecasting in the Mediterranean sea (opens in a new tab)

  4. Uncertainty and Generality of Transfer Learning Models in Predicting Signaling History

    … mesoderm lineages in mouse embryos. However, its predictions often show extremely high or extremely low confidence, suggesting a need for methods to prevent overconfidence and better account for uncertainty. To generalize IRIS to broader cell-cell communication problems, we combined engineering …

    mit Repository record for Uncertainty and Generality of Transfer Learning Models in Predicting Signaling History (opens in a new tab)

  5. Spatiotemporal Generalized Additive Model: Investigating Weather-Related Road Crashes in Southern Finland

    … 2017 to December 2021. The model employs MetCoOp Ensemble Prediction System (MEPS) data which was obtained from the Finnish Meteorological Institute. The constructed model explained 33.8% of the deviance and had good fit as per diagnostic plots of the randomized quantile residuals. The model …

    helsinki Repository record for Spatiotemporal Generalized Additive Model: Investigating Weather-Related Road Crashes in Southern Finland (opens in a new tab)

  6. Toward improved tropical cyclone intensity forecasts : probabilistic prediction, predictability, and the role of verification

    Over the past two decades, deterministic predictions of tropical cyclone (TC) intensity consistently scored poorly in mean absolute error (MAE) verification, despite the concurrent advancement of TC modeling and observing capabilities. Given the importance of understanding this situation for the …

    mit Repository record for Toward improved tropical cyclone intensity forecasts : probabilistic prediction, predictability, and the role of verification (opens in a new tab)

  7. Diabetes Mellitus Glucose Prediction by Linear and Bayesian Ensemble Modeling

    … glucose dynamics for the purpose of short-term prediction, developed within the EU FP7 DIAdvisor project. These models could, e.g., be used, in a decision support system, to alert the user of future low and high glucose levels, and, when implemented in a control framework, to suggest proactive …

    lund Repository record for Diabetes Mellitus Glucose Prediction by Linear and Bayesian Ensemble Modeling (opens in a new tab)

  8. Application of nonlinear dimensionality reduction to climate data for prediction

    … and simplification using a close system. Anyway, ensemble prediction techniques showed that the prediction skills of the three dimensional time series were as good as those found in much more complex models. This suggests that the climatological system in the tropics is mainly explained by ocean …

    potsdam-diss Repository record for Application of nonlinear dimensionality reduction to climate data for prediction (opens in a new tab)

  9. Traffic Signal Phase and Timing Prediction: A Machine Learning and Controller Logic Hybrid Approach

    … explores the different ways in which predictions can be made for the most likely switching times. Data are gathered from six intersections along the Gallows Road corridor in Northern Virginia. The application of long-short term memory neural networks for obtaining predictions is …

    vt Repository record for Traffic Signal Phase and Timing Prediction: A Machine Learning and Controller Logic Hybrid Approach (opens in a new tab)