NDLI: Adaptively perturbing localized state space in data assimilation of wildfire spread simulation

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Adaptively perturbing localized state space in data assimilation of wildfire spread simulation

Content Provider	ACM Digital Library
Author	Gu, Feng
Abstract	Real time data can be assimilated into the simulation model using sequential Monte Carlo (SMC) methods to improve the estimation of the wildfire spread simulation. The standard SMC methods algorithm uses a fixed number of particles and doesn't have run-time state inference estimation and particle convergence characterization. Therefore, the convergence of particles cannot be guaranteed and a large number of particles are required to ensure that the state space is effectively covered by the particles and the particles can converge to the true posterior of the system state. For wildfire spread simulation, the system has a large spatial state and its system behaviors are heterogeneous in different areas. This type of heterogeneous and spatial-temporal dynamic behavior results in non-uniform and dynamic changing uncertainty of state inference. In this paper, we develop the algorithm to adaptively perturb the localized state space to achieve more effective coverage of the state space. The experimental results show that more accurate results are obtained by adaptively perturbing the localized state space for data assimilation of wildfire spread simulation.
Starting Page	163
Ending Page	172
Page Count	10
File Format	PDF
ISBN	9781510800991
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-04-12
Publisher Place	San Diego
Access Restriction	Subscribed
Subject Keyword	Quantification Wildfire spread State inference Sequential monte carlo methods Data assimilation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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