L
Li Xiaoyong
Researcher at South China Normal University
Publications - 4
Citations - 113
Li Xiaoyong is an academic researcher from South China Normal University. The author has contributed to research in topics: Deep learning & Adsorption. The author has an hindex of 3, co-authored 4 publications receiving 36 citations.
Papers
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Journal ArticleDOI
A novel effluent quality predicting model based on genetic-deep belief network algorithm for cleaner production in a full-scale paper-making wastewater treatment
Guoqiang Niu,Xiaohui Yi,Xiaohui Yi,Chen Chen,Li Xiaoyong,Donghui Han,Bo Yan,Mingzhi Huang,Guang-Guo Ying +8 more
TL;DR: The genetic algorithm (GA) was employed to reduce the input variables dimensionality, simplify the network structure and overcome the dynamic characteristic difficulties of process data in monitoring to improve the predictive accuracy and reliability for process monitoring.
Journal ArticleDOI
Application of novel hybrid deep leaning model for cleaner production in a paper industrial wastewater treatment system
Li Xiaoyong,Xiaohui Yi,Xiaohui Yi,Zhenghui Liu,Hongbin Liu,Tao Chen,Guoqiang Niu,Bo Yan,Chen Chen,Mingzhi Huang,Guang-Guo Ying +10 more
TL;DR: In this article, a hybrid deep leaning CLSTMA model, which based on sequential fusion convolutional neural network (CNN), long short term memory (LSTM) and attention mechanism (AM), was developed to monitor the water quality in a full-scale paper industrial wastewater treatment system for energy conservation and emissions reduction.
Journal ArticleDOI
Accurate prediction and further dissection of neonicotinoid elimination in the water treatment by CTS@AgBC using multihead attention-based convolutional neural network combined with the time-dependent Cox regression model.
Chao Zhang,Thomas B. Kornberg,Li Xiaoyong,Feng Li,Gugong Li,Guoqiang Niu,Hongyu Chen,Guang-Guo Ying,Mingzhi Huang,Mingzhi Huang +9 more
TL;DR: In this paper, a multi-head attention (MHA)-based convolutional neural network (CNN) combined with the time-dependent Cox regression model are initially applied to predict and dissect the adsorption elimination processes of IMI by CTS@AgBC.
Journal ArticleDOI
Adaptation of methane recovery, sludge characteristics and evolution of microbial community response to elevated nitrate under the methanogenic condition
Xiaohui Yi,Renren Wu,Donghui Han,Yan Li,Li Xiaoyong,Guoqiang Niu,Mingzhi Huang,Guang-Guo Ying +7 more
TL;DR: In this paper, an experiment lasing about 300 days under the methanogenic condition with sequential influent nitrate addition as COD/NO3−-N ratio from 486.03 to 8.00 was carried out.