Soft sensor validation for monitoring and resilient control of sequential subway indoor air quality through memory-gated recurrent neural networks-based autoencoders | ||
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Jorge Loy-Benitez, SungKu Heo, ChangKyoo Yoo*, Soft sensor validation for monitoring and resilient control of sequential subway indoor air quality through memory-gated recurrent neural networks-based autoencoders, Control Engineering Practice (ISSN:, SCI, JCR Top 20% journal-Chem. Eng.), 97(4), 104330(pp.1-17) (2020.04) (Ack: Subway Fine Dust: 19QPPW-B152306-01 & 2017R1E1A1A03070713) |
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이전글 | A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea | |
다음글 | Soft sensor modeling of industrial process data using kernel latent variables-based relevance vector machine |