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在“自然资源管理”中，命中：53条，耗时：0.0309868 秒

1.Electrical Load Forecasting Using An Expanded Kalman Filter Bank Methodology

作者：Conor Lynch* ; conor.lynch@mycit.ie ; Michael J.O'Mahony** ; Michael.JOMahony@cit.ie ; Richard A. Guinee*** ; richardguinee@cit.ie

关键词：Kalman Filter ; Micro-grid ; Electrical Load Demand ; Forecasting

刊名：IFAC-PapersOnLine

年：2016

2.Real-time data assimilation for large-scale systems: The spectral Kalman filter

作者：Hojat Ghorbanidehno ; a ; hojjatgh@stanford.edu" class="auth_mail" title="E-mail the corresponding author ; ghorbani.hojatt@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Amalia Kokkinakib ; amaliak@stanford.edu" class="auth_mail" title="E-mail the corresponding author ; Judith Yue Lib ; yuel@stanford.edu" class="auth_mail" title="E-mail the corresponding author ; Eric Darvea ; c ; darve@stanford.edu" class="auth_mail" title="E-mail the corresponding author ; Peter K. Kitanidisb ; c ; peterk@stanford.edu" class="auth_mail" title="E-mail the corresponding author

关键词：Kalman filter ; Data assimilation ; CO2 monitoring ; Bayesian analysis ; Uncertainty quantification ; Fast Kalman filter

刊名：Advances in Water Resources

年：2015

3.Comparison of Ensemble Kalman Filter groundwater-data assimilation methods based on stochastic moment equations and Monte Carlo simulation

作者：M. Panzeria ; marco.panzeri@polimi.it" class="auth_mail ; M. Rivaa ; b ; A. Guadagninia ; b ; S.P. Neumanb

关键词：Ensemble Kalman Filter ; Random hydraulic conductivity field ; Moment equations ; Data assimilation ; Transient groundwater flow ; Filter inbreeding

刊名：Advances in Water Resources

年：April, 2014

4.Controlling the renewable microgrid using semidefinite programming technique

作者：Md Masud Rana ; mdmasud.rana@student.uts.edu.au" class="auth_mail" title="E-mail the corresponding author ; Li Li ; Steven W. Su

关键词：Communication network ; Distributed energy resource ; Kalman filter ; Semidefinite programming ; State estimation ; Optimal control strategy

刊名：International Journal of Electrical Power & Energy Systems

年：2017

5.Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation

作者：Gift Dumedah ; Paulin Coulibaly

关键词：Streamflow forecasting ; Data assimilation ; Evolutionary algorithms ; The ensemble Kalman filter ; The particle filter

刊名：Advances in Water Resources

年：2013

6.State estimation of tidal hydrodynamics using ensemble Kalman filter

作者：Hitoshi Tamura ; Peter Bacopoulos ; Dingbao Wang ; Scott C. Hagen ; Ethan J. Kubatko

关键词：DG ADCIRC-2DDI ; Ensemble Kalman filter ; State estimation ; Parallelized simulation ; Tides ; Hydrodynamics

刊名：Advances in Water Resources

年：January, 2014

7.Annual stream flow simulation by ARMA processes and prediction by Kalman filter

作者：Khadidja Boukharouba (1)

关键词：Kalman filter ; ARMA ; Prediction ; Stream flow ; B茅ni ; Badel ; Algeria

刊名：Arabian Journal of Geosciences

年：2013

8.An Experimental Study on Evapotranspiration Data Assimilation Based on the Hydrological Model

作者：Jian Yin ; Chesheng Zhan ; Wen Ye

关键词：Evapotranspiration ; Remote sensing ; Hydrological model ; Ensemble Kalman filter ; Data assimilation

刊名：Water Resources Management

出版者：Springer Netherlands

年：2016

9.Ensemble Kalman filter versus particle filter for a physically-based coupled surface-subsurface model

作者：Damiano Pasetto ; Matteo Camporese ; Mario Putti

关键词：Surface/subsurface water interactions ; CATHY Model ; Bayesian uncertainty evaluation ; Monte Carlo data assimilation ; SIR particle filter ; Ensemble Kalman filter

刊名：Advances in Water Resources

年：2012

10.Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering

作者：Mohamad El Gharamti ; Ibrahim Hoteit ; Johan Valstar

关键词：Flow and transport coupled models ; Ensemble Kalman filter ; Joint states estimation ; Dual states estimation

刊名：Advances in Water Resources

年：2013

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