Data-Driven Hybrid Model for Forecasting Wastewater Influent Loads Based on Multimodal and Ensemble Deep Learning | ||
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SungKu Heo, KiJeon Nam, Jorge Loy-Benitez, and ChangKyoo Yoo*, Data-Driven Hybrid Model for Forecasting Wastewater Influent Loads Based on Multimodal and Ensemble Deep Learning, IEEE Transactions on Industrial Informatics (ISSN:1551-3203, SCI, IF = 10.2, Top 1 journal: Engineering Industrial), IEEE, 17(10), pp.6925-6934, (2021.10) Ack: 2017R1E1A1A03070713& Graduate School specialized in Climate Change) |
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이전글 | Techno-economic assessment and smart management of an integrated fuel cell-based energy system with absorption chiller for power, hydrogen, heating, and cooling in an electrified railway network | |
다음글 | Intelligent sensor validation for sustainable influent quality monitoring in wastewater treatment plants using stacked denoising autoencoders |