A methodology to restructure a pipeline system for an oilfield in the mid to late stages of development. - Bohong Wang; Yongtu Liang; Jianqin Zheng; Tiantian Lei; Meng Yuan; Haoran Zhang 002 (Comput. Chem. Eng., 2018)

Robust Optimization for Emergency Scheduling of Oil Products After Disaster. - Zhengbing Li; Qi Liao 001; Haoran Zhang 002; Yongtu Liang; Jianqin Zheng; Rui Qiu; Xiaodan Shi (IEEE Access, 2019)

An online real-time estimation tool of leakage parameters for hazardous liquid pipelines. - Jianqin Zheng; Yuanhao Dai; Yongtu Liang; Qi Liao 001; Haoran Zhang 002 (Int. J. Crit. Infrastructure Prot., 2020)

Scheduling of a branched multiproduct pipeline system with robust inventory management. - Zhengbing Li; Yongtu Liang; Qi Liao 001; Ning Xu 014; Jianqin Zheng; Haoran Zhang 002 (Comput. Ind. Eng., 2021)

Deeppipe: a customized generative model for estimations of liquid pipeline leakage parameters. - Jianqin Zheng; Yongtu Liang; Ning Xu 014; Bohong Wang; Taicheng Zheng; Zhengbing Li; Qi Liao 001; Haoran Zhang 002 (Comput. Chem. Eng., 2021)

PM2.5 Concentration Forecasting over the Central Area of the Yangtze River Delta Based on Deep Learning Considering the Spatial Diffusion Process. - Mingyue Lu; Tengfei Lao; Manzhu Yu; Yadong Zhang; Jianqin Zheng; Yuchen Li (Remote. Sens., 2021)

Deeppipe: A hybrid model for multi-product pipeline condition recognition based on process and data coupling. - Chang Wang; Jianqin Zheng; Yongtu Liang; Miao Li; Wencai Chen; Qi Liao 001; Haoran Zhang 002 (Comput. Chem. Eng., 2022)

A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants. - Jian Du; Jianqin Zheng; Yongtu Liang; Qi Liao 001; Bohong Wang; Xu Sun; Haoran Zhang 002; Maher Azaza; Jinyue Yan (Eng. Appl. Artif. Intell., 2023)

Review on intelligent pipeline technologies: A life cycle perspective. - Zhuochao Li; Yongtu Liang; Youyi Liang; Qi Liao 001; Bohong Wang; Liqiao Huang; Jianqin Zheng; Haoran Zhang 002 (Comput. Chem. Eng., 2023)

A Knowledge-Inspired Hierarchical Physics-Informed Neural Network for Pipeline Hydraulic Transient Simulation. - Jian Du; Haochong Li; Qi Liao 001; Jun Shen 001; Jianqin Zheng; Yongtu Liang (CoRR, 2024)

A physics-enhanced multi-modal fused neural network for predicting contamination length interval in pipeline. - Jian Du; Pengtao Niu; Jianqin Zheng; Qi Liao 001; Yongtu Liang (CoRR, 2024)

DeepPipe: A multi-stage knowledge-enhanced physics-informed neural network for hydraulic transient simulation of multi-product pipeline. - Jian Du; Haochong Li; Kaikai Lu; Jun Shen 001; Qi Liao 001; Jianqin Zheng; Rui Qiu; Yongtu Liang (J. Ind. Inf. Integr., 2024)