Results 91 to 100 of about 39,931 (297)
Nowcasting World Trade With Machine Learning: A Three‐Step Approach
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn +2 more
wiley +1 more source
This work demonstrates the potential of the assimilation of satellite solar‐induced fluorescence (SIF) retrievals at eight‐day and 0.1° resolutions in the integrated forecast system (IFS), developed at the European Centre for Medium‐Range Weather Forecasts (ECMWF), at global scale, to provide a more realistic representation of the vegetation temporal ...
Sébastien Garrigues +12 more
wiley +1 more source
Adaptive Robust Extended Kalman Filter
The AREKF is proposed here as a modification of the REKF, that switches between the REKF mode and the normal EKF mode under the control of the innovation. In the presence of large external disturbances, the proposed algorithm is more effective than the REKF to ensure boundedness of the estimation error. On the other hand, in the absence of disturbances,
Xiong, Kai +2 more
openaire +3 more sources
Though many studies have shown potential benefit in assimilating all‐sky infrared radiances from geostationary satellites, at numerical weather prediction centres it is still common practice to assimilate clear‐sky radiances. We present the operationalization of the all‐sky assimilation of the spinning enhanced visible and infrared imager (SEVIRI ...
Annika Schomburg +5 more
wiley +1 more source
This article demonstrates that assimilating machine‐learning‐derived surface nitrate can improve five‐day phytoplankton forecast substantially within the Met Office operational system for the Northwest European Shelf. We explain the reasons behind this improvement and propose that an online system where machine learning and data assimilation are cycled
Deep S. Banerjee +2 more
wiley +1 more source
The Kalman filter is one of the best-known and most frequently used methods for dynamic state estimation. In addition to a measurement and state transition model, the Kalman filter requires knowledge about the covariance of the measurement and process ...
Theresa Kruse +2 more
doaj +1 more source
Investigations of an Aboriginal Whaling Management Procedure using Adaptive Kalman Filtering
Kjartan G. Magnússon +1 more
openalex +2 more sources
Extended Kalman Filter Based Fuzzy Adaptive Filter
Fundamentals of fuzzy logic, fuzzy logic system, equalizer, adaptive equalizer and fuzzy adaptive equalizer are described in this chapter. A new fuzzy adaptive equalizer with extended Kalman filter adaptation (EKFAE) had been derived in this chapter for communication channel equalization.
Wong, Wai Kit, Lim, Heng Siong
openaire +3 more sources
Nonlinear and adaptive estimation techniques in reentry [PDF]
The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported.
Flanagan, P. +3 more
core +1 more source
The study evaluates five factors affecting the assimilation of surface‐sensitive Advanced Microwave Sounding Unit‐A (AMSU‐A) radiances over land, including the simultaneous estimation of surface emissivity and the standard set of state variables, to improve numerical weather prediction (NWP) at Environment and Climate Change Canada (ECCC).
Zheng Qi Wang +4 more
wiley +1 more source

