Imperial College London
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DrRossellaArcucci

Faculty of Engineering, Department of Earth Science & Engineering

Senior Lecturer in Data Science and Machine Learning
 
 
 
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Contact

 

r.arcucci Website

 
 
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Location

 

Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zhu:2019:10.26599/bdma.2018.9020033,
author = {Zhu, J and Hu, S and Arcucci, R and Xu, C and Zhu, J and Guo, Y-K},
doi = {10.26599/bdma.2018.9020033},
journal = {Big Data Mining and Analytics},
pages = {83--91},
title = {Model error correction in data assimilation by integrating neural networks},
url = {http://dx.doi.org/10.26599/bdma.2018.9020033},
volume = {2},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - In this paper, we suggest a new methodology which combines Neural Networks (NN) into Data Assimilation (DA). Focusing on the structural model uncertainty, we propose a framework for integration NN with the physical models by DA algorithms, to improve both the assimilation process and the forecasting results. The NNs are iteratively trained as observational data is updated. The main DA models used here are the Kalman filter and the variational approaches. The effectiveness of the proposed algorithm is validated by examples and by a sensitivity study.
AU  - Zhu,J
AU  - Hu,S
AU  - Arcucci,R
AU  - Xu,C
AU  - Zhu,J
AU  - Guo,Y-K
DO  - 10.26599/bdma.2018.9020033
EP  - 91
PY  - 2019///
SN  - 2096-0654
SP  - 83
TI  - Model error correction in data assimilation by integrating neural networks
T2  - Big Data Mining and Analytics
UR  - http://dx.doi.org/10.26599/bdma.2018.9020033
VL  - 2
ER  -
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