Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter
In this paper, new method is proposed for a more robust Data Assimilation (DA) design of the river flow and stage estimation. By using the new sets of data that are derived from the incorporated Multi Imputation Particle Filter (MIPF) in the DA structure, the proposed method is found to have overc...
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2019
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| Online Access: | http://eprints.uthm.edu.my/4045/1/J11909_38ca1c621876c8a34ba9703cfeed20a1.pdf http://eprints.uthm.edu.my/4045/ |
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| author | Ismail, Zool Hilmi Jalaludin, Nor Anija |
| author_facet | Ismail, Zool Hilmi Jalaludin, Nor Anija |
| author_sort | Ismail, Zool Hilmi |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, new method is proposed for a more robust Data Assimilation (DA) design of the
river flow and stage estimation. By using the new sets of data that are derived from the incorporated Multi
Imputation Particle Filter (MIPF) in the DA structure, the proposed method is found to have overcome the
issue of missing observation data and contributed to a better estimation process. The convergence analysis
of the MIPF is discussed and shows that the number of the particles and imputation influence the ability of
this method to perform estimation. The simulation results of the MIPF demonstrated the superiority of the
proposed approach when being compared to the Extended Kalman Filter (EKF) and Particle Filter (PF). |
| format | Article |
| id | my.uthm.eprints-4045 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2019 |
| publisher | IEEE |
| record_format | eprints |
| spelling | my.uthm.eprints-40452021-11-24T01:17:38Z http://eprints.uthm.edu.my/4045/ Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter Ismail, Zool Hilmi Jalaludin, Nor Anija QA273-280 Probabilities. Mathematical statistics In this paper, new method is proposed for a more robust Data Assimilation (DA) design of the river flow and stage estimation. By using the new sets of data that are derived from the incorporated Multi Imputation Particle Filter (MIPF) in the DA structure, the proposed method is found to have overcome the issue of missing observation data and contributed to a better estimation process. The convergence analysis of the MIPF is discussed and shows that the number of the particles and imputation influence the ability of this method to perform estimation. The simulation results of the MIPF demonstrated the superiority of the proposed approach when being compared to the Extended Kalman Filter (EKF) and Particle Filter (PF). IEEE 2019 Article PeerReviewed text en http://eprints.uthm.edu.my/4045/1/J11909_38ca1c621876c8a34ba9703cfeed20a1.pdf Ismail, Zool Hilmi and Jalaludin, Nor Anija (2019) Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter. IEEE Access, 7. |
| spellingShingle | QA273-280 Probabilities. Mathematical statistics Ismail, Zool Hilmi Jalaludin, Nor Anija Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter |
| title | Robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| title_full | Robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| title_fullStr | Robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| title_full_unstemmed | Robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| title_short | Robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| title_sort | robust data assimilation in river flow and
stage estimation based on multiple
imputation particle filter |
| topic | QA273-280 Probabilities. Mathematical statistics |
| url | http://eprints.uthm.edu.my/4045/1/J11909_38ca1c621876c8a34ba9703cfeed20a1.pdf http://eprints.uthm.edu.my/4045/ |
| url_provider | http://eprints.uthm.edu.my/ |