Ensemble-Based Data Assimilation MethodsEnsemble-based methods have become very popular for data assimilation in numerical models of oceanic or atmospheric flows. Unlike the deterministic Extended Kalman Filter which explicitly describes thPierre Brasseur...
the design of ensemble methods. This work shows that it provides a theoretical and practical tool to develop new ensemble methods well-tuned to the characteristics of a specific base learner. On the basis of the analysis and experiments performed on SVMs and bagged ensembles of ...
A novel localization scheme for scalar uncertainties in ensemble-based data assimilation methodsHistory matchingES-MDADistance-dependent localizationNon-distance-dependent localizationCorrelation-based adaptive localizationHistory matching, also known as data assimilation, is an inverse problem with multiple ...
分布的转变涉及到了输出分布很大的变化,对现有的模型造成一个很大级别的瑕疵。 3 Methods 这一节描述了我们的方法的两个阶段(1)建立一个只有偏差的模型和(2)使用它通过集合训练一个健壮的模型。 3.1 Training a Bias-Only Model 第一阶段的目标是建立一个在训练数据上表现良好的模型,但在域外测试集上表现可能很...
Ensemble-based anomaly detection methods still face some challenges, however, such as data imbalance, time and space demand and the selection of base detectors. To this end, we propose a selective ensemble method for anomaly detection based on parallel learning (SEAD-PL). First, a differentiated...
The methods for solving the class imbalance task can generally be divided into two categories: sampling approaches and algorithmic approaches. The sampling approach is factually a re-sizing procedure to balance the given imbalance dataset. The algorithmic approach can be viewed as a procedure to adju...
Each method is evaluated on two large, real datasets, and then the effective methods are combined to form a cascade MF ensemble scheme. The validation results on experiment datasets demonstrate that compared to a single MF-based recommender, our ensemble scheme could obtain a significant improvement...
Although new ensemble-based methods to account for uncertainty in short term quantitative precipitation forecasts (QPF's) are being developed, methods to account for uncertainty in existing short term deterministic QPF's are needed for immediate application in AHPS. Existing ensemble streamflow prediction...
Some research finds the efficacy of signature-based methods, which rely on predefined patterns to flag known botnet traffic. While this approach has demonstrated proficiency in recognizing established threats, it fundamentally lacks the flexibility to adapt to the polymorphic nature of contemporary botnets...
Tree-based ensemble methods and their applications in analytical chemistry[J] . Dong-Sheng Cao,Jian-Hua Huang,Yi-Zeng Liang.Trends in Analytical Chemistry . 2012D.-S. Cao, J.-H. Huang, Y.-Z. Liang, Q.-S. Xu, L.-X. Zhang, Tree-based ensemble methods and their applications in ...