Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/87935
Title: | An approach for filter divergence suppression in a sequential data assimilation system and its application in short-term traffic flow forecasting | Authors: | Tong, X Wang, R Shi, W Li, Z |
Issue Date: | 2020 | Source: | ISPRS international journal of geo-information, 2020, v. 9, no. 6, ijgi9060340 | Abstract: | Mathematically describing the physical process of a sequential data assimilation system perfectly is difficult and inevitably results in errors in the assimilation model. Filter divergence is a common phenomenon because of model inaccuracies and affects the quality of the assimilation results in sequential data assimilation systems. In this study, an approach based on an L1-norm constraint for filter-divergence suppression in sequential data assimilation systems was proposed. The method adjusts the weights of the state-simulated values and measurements based on new measurements using an L1-norm constraint when filter divergence is about to occur. Results for simulation data and real-world traffic flow measurements collected from a sub-area of the highway between Leeds and Sheffield, England, showed that the proposed method produced a higher assimilation accuracy than the other filter-divergence suppression methods. This indicates the effectiveness of the proposed approach based on the L1-norm constraint for filter-divergence suppression. | Keywords: | Filter divergence Gain matrix L1-norm constrained Sequential data assimilation system Short-term traffic flow forecasting |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | ISPRS international journal of geo-information | EISSN: | 2220-9964 | DOI: | 10.3390/ijgi9060340 | Rights: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The following publication Tong X, Wang R, Shi W, Li Z. An Approach for Filter Divergence Suppression in a Sequential Data Assimilation System and Its Application in Short-Term Traffic Flow Forecasting. ISPRS International Journal of Geo-Information. 2020; 9(6):340, is available at https://doi.org/10.3390/ijgi9060340 |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Tong_approach_filter_divergence.pdf | 1.19 MB | Adobe PDF | View/Open |
Page views
50
Last Week
0
0
Last month
Citations as of Apr 28, 2024
Downloads
11
Citations as of Apr 28, 2024
SCOPUSTM
Citations
1
Citations as of Apr 26, 2024
WEB OF SCIENCETM
Citations
1
Citations as of Apr 25, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.