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Big Data Mining and Analytics  2019, Vol. 2 Issue (2): 83-91    DOI: 10.26599/BDMA.2018.9020033
    
Model Error Correction in Data Assimilation by Integrating Neural Networks
Jiangcheng Zhu, Shuang Hu, Rossella Arcucci, Chao Xu, Jihong Zhu, Yi-ke Guo*
Jiangcheng Zhu and Chao Xu are with State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Shuang Hu and Jihong Zhu are with Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.
Rossella Arcucci and Yi-ke Guo are with Data Science Institute, Imperial College London, London SW7 2AZ, UK.
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Abstract  

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.



Key wordsdata assimilation      deep learning      neural networks      Kalman filter      variational approach     
Received: 05 July 2018      Published: 06 January 2020
Corresponding Authors: Yi-ke Guo   
About author:

? Jiangcheng Zhu and Shuang Hu contribute equally to this paper. This work was done when they were visiting researchers in Data Science Institute, Imperial College London, London SW7 2AZ, UK.

Cite this article:

Jiangcheng Zhu, Shuang Hu, Rossella Arcucci, Chao Xu, Jihong Zhu, Yi-ke Guo. Model Error Correction in Data Assimilation by Integrating Neural Networks. Big Data Mining and Analytics, 2019, 2(2): 83-91.

URL:

http://bigdata.tsinghuajournals.com/10.26599/BDMA.2018.9020033     OR     http://bigdata.tsinghuajournals.com/Y2019/V2/I2/83

Fig. 1 Schematic diagram of DA+NN.
Fig. 2 Fully-connected neural network.
Fig. 3 Simulation result of DA+NN on double-integral system. The vertical dash-lines refer to the training windows.
Fig. 4 Result of data assimilation with NN on Lorenz system.
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