Enhancing state and parameter estimations of a dynamic crop model by a recombination particle filter
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Enhancing state and parameter estimations of a dynamic crop model by a recombination particle filter
Authors
Keywords
-
Journal
COMPUTERS AND ELECTRONICS IN AGRICULTURE
Volume 214, Issue -, Pages 108355
Publisher
Elsevier BV
Online
2023-10-31
DOI
10.1016/j.compag.2023.108355
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Multi-variable assimilation into a modified AquaCrop model for improved maize simulation without management or crop phenology information
- (2022) Yang Lu et al. AGRICULTURAL WATER MANAGEMENT
- Data assimilation with sensitivity-based particle filter: A simulation study with AquaCrop
- (2022) Yevgeniya Orlova et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Assimilation of soil moisture and canopy cover data improves maize simulation using an under-calibrated crop model
- (2021) Yang Lu et al. AGRICULTURAL WATER MANAGEMENT
- Remote Sensing Data Assimilation in Dynamic Crop Models Using Particle Swarm Optimization
- (2020) Matthias P. Wagner et al. ISPRS International Journal of Geo-Information
- State and parameter estimation of the AquaCrop model for winter wheat using sensitivity informed particle filter
- (2020) Tianxiang Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Genetic Operator-Based Particle Filter Combined with Markov Chain Monte Carlo for Data Assimilation in a Crop Growth Model
- (2020) Alaa Jamal et al. Agriculture-Basel
- Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices
- (2019) Jibo Yue et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Bayesian calibration of AquaCrop model for winter wheat by assimilating UAV multi-spectral images
- (2019) Tianxiang Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Enhancing hydrologic data assimilation by evolutionary Particle Filter and Markov Chain Monte Carlo
- (2018) Peyman Abbaszadeh et al. ADVANCES IN WATER RESOURCES
- A review of data assimilation of remote sensing and crop models
- (2018) Xiuliang Jin et al. EUROPEAN JOURNAL OF AGRONOMY
- Fight sample degeneracy and impoverishment in particle filters: A review of intelligent approaches
- (2014) Tiancheng Li et al. EXPERT SYSTEMS WITH APPLICATIONS
- Application of Crop Model Data Assimilation With a Particle Filter for Estimating Regional Winter Wheat Yields
- (2014) Zhiwei Jiang et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation
- (2013) Gift Dumedah et al. ADVANCES IN WATER RESOURCES
- Global sensitivity analysis of yield output from the water productivity model
- (2013) Eline Vanuytrecht et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Examining the effectiveness and robustness of sequential data assimilation methods for quantification of uncertainty in hydrologic forecasting
- (2012) Caleb M. DeChant et al. WATER RESOURCES RESEARCH
- Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method
- (2012) Hamid Moradkhani et al. WATER RESOURCES RESEARCH
- Local density adaptive similarity measurement for spectral clustering
- (2010) Xianchao Zhang et al. PATTERN RECOGNITION LETTERS
- Particle Filtering in Geophysical Systems
- (2009) Peter Jan van Leeuwen MONTHLY WEATHER REVIEW
- Obstacles to High-Dimensional Particle Filtering
- (2008) Chris Snyder et al. MONTHLY WEATHER REVIEW
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now