Data Driven Computing by the Morphing Fast Fourier Transform Ensemble Kalman Filter in Epidemic Spread Simulations
Computation
2010-03-10 v1 Quantitative Methods
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.
Keywords
Cite
@article{arxiv.1003.1771,
title = {Data Driven Computing by the Morphing Fast Fourier Transform Ensemble Kalman Filter in Epidemic Spread Simulations},
author = {Jan Mandel and Jonathan D. Beezley and Loren Cobb and Ashok Krishnamurthy},
journal= {arXiv preprint arXiv:1003.1771},
year = {2010}
}
Comments
11 pages, 3 figures. Submitted to ICCS 2010