Open Access
| Issue |
E3S Web of Conf.
Volume 406, 2023
2023 9th International Conference on Energy Materials and Environment Engineering (ICEMEE 2023)
|
|
|---|---|---|
| Article Number | 04028 | |
| Number of page(s) | 4 | |
| Section | Geographic Remote Sensing Application and Environmental Modeling | |
| DOI | https://doi.org/10.1051/e3sconf/202340604028 | |
| Published online | 31 July 2023 | |
- Brosilow Joseph B. (1978) Inferential Control of Process, PART I, Steady State Analysis and Design[J]. Rims Kokyuroku, 757(3):35–66. [Google Scholar]
- Shao W. M., Ge Z. Q, Song Z. H. (2019) Semi- supervised dynamic Soft sensing Modeling Method based on cyclic neural network [J]. Journal of Electronic Measurement and Instrument, 33(11):7–13. (In Chinese) [Google Scholar]
- Sang H., Li J. (2016) Soft sensing Modeling Method of Chemical Process Based on Elman Neural Network [J]. Automatic Instrument, 37(03):69–73. [Google Scholar]
- Fortuna L, Graziani S, Rizzo A,et al.(2007) Soft sensors for monitoring and control of industrial processes[M].Berlin: Springer. [Google Scholar]
- Sun Q., Ge Z. (2019) Probabilistic Sequential Network for Deep Learning of Complex Process Data and Soft Sensor Application[J]. IEEE Transactions on Industrial Informatics, 15(5):2700–2709. [CrossRef] [Google Scholar]
- Song S, Lam J, Han Y, et al. (2020) ResNet-LSTM for Real-time PM2.5 and PM10 Estimation Using Sequential Smartphone Images[J]. IEEE Access, 8: 220069–220082. [CrossRef] [Google Scholar]
- Tsinghua W K, Huang D, Fan Y, et al. (2017) Soft sensor development and applications based on LSTM in deep neural networks[C]. IEEE Symposium Series on Computational Intelligence (SSCI). Hawaii: 1–6. [Google Scholar]
- Nelle’s O. (2001) Nonlinear system identification: from classical approaches to neural[J]. Applied Therapeutics, 6(7):717–21. [Google Scholar]
- Zheng R J. (2020) Study on Soft Sensing Modeling of glutamic acid fermentation process [D]. Jiangnan University. (In Chinese) [Google Scholar]
- Yuan X.F., Li L, Wang Y.L. (2020) Nonlinear Dynamic Soft Sensor Modeling with Supervised Long Short-Term Memory Network[J]. IEEE Transactions on Industrial Informatics, 3168–3176. [Google Scholar]
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