The performance of single models and ensemble prediction systems has been investigated with respect to quantitative precipitation forecasts. Evaluation is based on the potential economic value of +72 h/+96 h forecasts. The verification procedure consists of taking into account all precipitation amounts that are predicted in the vicinity of an observation in order to compute spatial, multi-event...

One of the crucial aspects of the design of an ensemble prediction system is the definition of the ensemble of initial states. This work investigates the use of singular vectors, an ensemble of analyses, and a combination of the two types of perturbations in the ECMWF operational ensemble prediction system. First, the similarity between perturbations generated using initialtime singular vectors...

Dynamic (also known as instance-based) ensemble pruning, selects a (potentially) different subset of models from an ensemble during prediction based on the given unknown instance with the goal of maximizing prediction accuracy. This paper models dynamic ensemble pruning as a multi-label classification task, by considering the members of the ensemble as labels. Multi-label training examples are ...

In this paper ensemble learning based feature selection and classifier ensemble model is proposed to improve classification accuracy. The hypothesis is that good feature sets contain features that are highly correlated with the class from ensemble feature selection to SVM ensembles which can be achieved on the performance of classification accuracy. The proposed approach consists of two phases:...

Behavioral research has demonstrated that the shape and texture of single objects can be processed independently. Similarly, neuroimaging results have shown that an object's shape and texture are processed in distinct brain regions with shape in the lateral occipital area and texture in parahippocampal cortex. Meanwhile, objects are not always seen in isolation and are often grouped together as...

Tropical Cyclone (TC) intensity forecasts are impacted by errors in atmosphere and ocean initial conditions and the model formulation, which motivates using an ensemble approach. This study evaluates the impact of uncertainty in atmospheric and oceanic initial conditions, as well as stochastic representations of the drag (Cd) and enthalphy (Ck) exchange coefficients on ensemble Advanced Hurrica...

in this study, the effective parameters on the inelastic response of asymmetric buildings is evaluated for an ensemble of real iranian earthquake records by considering soil-structure interaction. then, the design eccentricity obtained from the inelastic dynamic soil-structure analysis is compared with the design eccentricity of seisimic codes of iran, atc-3, new zeland, canada, mexico, austral...

To achieve well calibrated probabilistic forecasts, ensemble forecasts often need to be statistically post-processed. One recent ensemble-calibration method is extended logistic regression which extends the popular logistic regression to yield full probability distribution forecasts. Although the purpose of this method is to post-process ensemble forecasts, mostly only the ensemble mean is used...

Keywords: Ensemble pruning Backtracking algorithm Ensemble Pruning via BackTracking algorithm (EnPBT) One-Path and Two-Trips searching algorithm (OPTT) Pruning efficiency a b s t r a c t Ensemble pruning is substantial for the successful application of an ensemble system. A novel method for Ensemble Pruning via BackTracking algorithm (EnPBT) was proposed by us in our previous work. Back-trackin...

A Deformed Gaussian Orthogonal Ensemble (DGOE) which interpolates between the Gaussian Orthogonal Ensemble and a Poissonian Ensemble is constructed. This new ensemble is then applied to the analysis of the chaotic properties of the low lying collective states of nuclei described by the Interacting