K. Wikle, "Understanding the ensemble Kalman filter," The American Statistician, pp. 350-357, Feb. 2016.Katfuss, M., Stroud, J. R., and Wikle, C. K. (2016). Understanding the ensemble kalman filter. The American Statistician 70, 350-357....
aReservoir history matching and inversion using an iterative ensemble Kalman filter with covariance localization 水库历史匹配和反向使用重申合奏Kalman过滤器以协变性地方化 [translate] a在我看来,适当的玩游戏可以调节心情,但是不要花费太多的时间 正在翻译,请等待... [translate] a影响着每个人的生活 Is ...
Ensemble Kalman Filter Data Assimilation with the ParFlow Hydrologic Model Hydrometeorological research has shown that simulations of atmospheric processes benefit from sophisticated land surface formulations. Moisture and energy ... JLI Williams - Agu Fall Meeting 被引量: 0发表: 2015年 ...
partitioned into surface soil moisture, root zone soil moisture, and shallow groundwater, spatially downscaled to 0.125° spatial resolution and temporally downscaled to the weekly time step using the using the Catchment Land Surface Model and an ensemble Kalman filter approach (Houborg et al., ...
Yi et al. 2019 Speed, acceleration √ GPS, accelerometer, gyroscope Decision trees, KNN, SVM, ensemble learning Normal, Aggressive, Drowsy *DTW: Dynamic Time Wrap, GMM: Gaussian Mixture Model, KNN: k-nearest neighbors, SVM: Support Vector Machines. 5.1. Statistical methods Some researchers attem...
soil layer thickness and initial value) on soil moisture estimation were evaluated based on the unscented weighted ensemble Kalman filter (UWEnKF) and a one-dimensional vertical water flow model at the ELBARA field site in the Maqu monitoring network in the upper reaches of the Yellow River, Ch...
When a TC is a threat to society, the Rapid-Scan mode is often activated to allow more vectors to be derived spatially and temporally. In this study, CIMSS hourly and Rapid-Scan AMVs are assimilated into the Weather Research and Forecasting (WRF) model using the Ensemble Kalman Filter (...
moisture and temperature states which were derived from three different products: Global Forecast System analyses, the National Center for Atmospheric Research (NCAR) continuously cycling ensemble Kalman filter (EnKF) data assimilation system, and the North American Land Data Assimilation System (NLDAS-2...
The bus service reliability fluctuates largely in the peak hours, especially the morning peak. Bus bunching and large bus time headway easily occur, and once it occurs, it will continue until destination. The Kalman filter-LSTM model outperforms the ensemble learning methods to predict travel time...