Data driven computing by the morphing fast Fourier transform ensemble Kalman filter in epidemic spread simulations
Year: 2010
Type: conference-paper
Abstract: The FFT EnKF data assimilation method is proposed and applied to a stochastic cell simulation of an epidemic, based on the S-I-R spread model. The FFT EnKF combines spatial statistics and ensemble filtering methodologies into a localized and computationally inexpensive version of EnKF with a very small ensemble, and it is further combined with the morphing EnKF to assimilate changes in the position of the epidemic.
Source: Procedia Computer Science
Institution: University of Colorado Denver
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: diamond
Awards: G4309232636, G4624045957, Improved Tracking for Emerging Diseases from Climate Change, CSR-CSI: Collaborative Research: Dynamic Sensor/Computation Network for Wildfire Management, G6530889380, Collaborative Research: CDI-Type II--The Open Wildland Fire Modeling E-community: A Virtual Organization Accelerating Research, Education, and Fire Management Technology, G8186554587
OpenAlex ID: W2131286733