Dynamic Data Reconciliation of Gas Turbine Based on PCA-LSTM

Author:

Ren Dezhi,Cao Yunpeng,Li Shuying

Publisher

Springer Nature Switzerland

Reference11 articles.

1. Bai, Y., Yan, B., Zhou, C., et al.: State of art on state estimation: kalman filter driven by machine learning. Annu. Rev. Control. 56, 100909 (2023)

2. Jiang, Y., Liu, A.: Dynamic data reconciliation based on constrained strong tracking filter. CIESC J. 62(6), 1626–1632 (2011)

3. Prakash, J., Anbumalar, P.: An improved recursive non-linear dynamic data reconciliation for non-linear state estimation subject to bound constraints. Int. J. Adv. Eng. Sci. Appl. Math. 15(10), 1–9 (2023)

4. Bai, S., McLean, D., Thibault, J.: Autoassociative neural networks for robust dynamic data reconciliation. Aiche J. 53, 438–448 (2007)

5. Xie, S., Wang, H., Peng, J.: Energy efficiency analysis and optimization of industrial processes based on a novel data reconciliation. IEEE Access 9, 47436–47451 (2021)

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