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Systems Science & Control Engineering
An Open Access Journal
Volume 11, 2023 - Issue 1
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Review

A review: state estimation based on hybrid models of Kalman filter and neural network

Shuo Fenga School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;b Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of ChinaCorrespondence[email protected]
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Xuegui Lia School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;b Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of China;d Sanya Offshore Oil & Gas Research Institute, Northeast Petroleum University, Sanya, People's Republic of ChinaView further author information
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Shuai Zhanga School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;b Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of ChinaView further author information
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Zhen Jiana School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of ChinaView further author information
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Hanxu Duana School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;b Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of ChinaView further author information
&
Zepeng Wanga School of Computer & Information Technology, Northeast Petroleum University, Daqing, People's Republic of China;b Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing, People's Republic of China;c Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing, People's Republic of ChinaView further author information
Article: 2173682 | Received 26 Oct 2022, Accepted 24 Jan 2023, Published online: 09 Feb 2023

Figures & data

Figure 1. State estimation methods.

Figure 1. State estimation methods.

Figure 2. Hybrid models for state estimation.

Figure 2. Hybrid models for state estimation.

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