A novel effluent quality predicting model based on genetic-deep belief networkalgorithm for cleaner production in a full-scale paper-making wastewatertreatment， Journal of Cleaner Production 265 (2020)121787(共同一作，SCI 中科院一区)
Application of novel hybrid deep learning model for cleaner production in apaper industrial wastewater treatment system. Journal of Cleaner Production,294(2021), 126343 (一作，SCI 中科院一区)
Accurate prediction and furtherdissection of neonicotinoid elimination in the water treatment by CTS@AgBC using multihead attention-based convolutional neuralnetwork combined with the time-dependent Cox regression model. Journalof Hazardous Materials,423(2022),127029 (共同一作，SCI 中科院一区)
Dynamic optimization of wastewater treatment process based on novel multi-objective ant lion optimization and deep learning algorithm. Journal of Cleaner Production,345(2022), 131140(共同一作，SCI 中科院一区)
Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system. Environmental Research, 211(2022), 112942(共同一作，SCI 中科院一区)
A novel pedal musculoskeletal response based on differential spatio-temporal LSTM for human activity recognition. Knowledge-Based Systems 261 (2023): 110187.(二作，SCI 中科院一区)
The LPST-Net: A new deep interval health monitoring and prediction framework for bearing-rotor systems under complex operating conditions. Advanced Engineering Informatics, 62(2024),102558(通讯作者，SCI 中科院一区)
Application of deep learning model based on transfer learning in activated sludge process for wastewater purification. Journal of Water Process Engineering, 59, (2024),104902(一作，SCI 中科院二区)
Prediction performance and reliability evaluation of three ginsenosides in Panax ginseng using hyperspectral imaging combined with a novel ensemble chemometric model. Food Chemistry, 430, (2023),136917(四作，SCI 中科院一区)
A hybrid CLSTM-GPR model for forecasting particulate matter (PM2.5). Atmospheric Pollution Research, 14, (2023),101832(共同一作，SCI 中科院三区)
Application of Residual Structure Time Convolutional Network Based on Attention Mechanism in Remaining Useful Life Interval Prediction of Bearings. Sensors (Basel). 2024,24(13):4132. (通讯作者，SCI 中科院三区)