[1] Qiao Junfei, Sun Zijian,Meng Xi*. A comprehensively improved interval type-2 fuzzy neural network for NOx emissions prediction in MSWI process. IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2023.3245640.

[2] Qiao Junfei, Sun Zijian,Meng Xi*. Interval type-2 fuzzy neural network based on active semi-supervised learning for non-stationary industrial processes. IEEE Transactions on Automation Science and Engineering, doi: 10.1109/TASE.2023.3237840.

[3] Qiao Junfei, Sun Jian,Meng Xi*. Event-triggered adaptive model predictive control of oxygen content for municipal solid waste incineration process. IEEE Transactions on Automation Science and Engineering, doi: 10.1109/TASE.2022.3227918.

[4] Qiao Junfei, Zhou Jianglong,Meng Xi*.A multi-task learning model for the prediction of NOx emissions in municipal solid waste incineration processes.IEEE Transactions on Instrumentation and Measurement,2023, 72:1-14.

[5]Meng Xi, Tang Jian, Qiao Junfei*. NOxemissions prediction with a brain-inspired modular neural network in municipal solid waste incineration processes. IEEE Transactions on Industrial Informatics,2022,18(7): 4622-4631.

[6]Meng Xi*, Zhang Yin, Qiao Junfei. An adaptive task-oriented RBF network for key water quality parameters prediction in wastewater treatment process. Neural Computing and Applications, 2021, 33(17): 11401-11414.

[7] Sun Jian,Meng Xi, Qiao Junfei*. Prediction of oxygen content using weighted PCA and improved LSTM network in MSWI process. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-12.

[8] Qiao Junfei,Meng Xi*, Li Wenjing., Bogdan M Wilamowski. A novel modular RBF neural network based on a brain-like partition method. Neural Computing and Applications, 2020, 32(1): 899–911.

[9]Meng Xi, Pawel Rozycki, Qiao Junfei*, Bogdan M Wilamowski. Nonlinear system modeling using RBF networks for industrial application. IEEE Transactions on Industrial Informatics, 2018, 14(3): 931-940.