Jianqin Zheng

发表

Deeppipe: Theory-guided neural network method for predicting burst pressure of corroded pipelines

J. Klemeš, Yunlu Ma, Jianqin Zheng, 2022, Process Safety and Environmental Protection.

Deeppipe: An intelligent monitoring framework for operating condition of multi-product pipelines

J. Klemeš, Jianqin Zheng, Yongtu Liang, 2022, Energy.

A safety management system for natural gas pipeline in subsidence area of coal mine

Jianqin Zheng, Yongtu Liang, Bohong Wang, 2022, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.

Innovations of carbon-neutral petroleum pipeline: A review

H. Zhang, Jianqin Zheng, Yongtu Liang, 2022, Energy Reports.

Weather condition-based hybrid models for multiple air pollutants forecasting and minimisation

J. Klemeš, Jianqin Zheng, Yongtu Liang, 2022, Journal of Cleaner Production.

Planning of a flexible refined products transportation network in response to emergencies

J. Klemeš, Jianqin Zheng, Bohong Wang, 2021, Journal of Pipeline Science and Engineering.

A hybrid deep learning framework for predicting daily natural gas consumption

Petar Sabev Varbanov, J. Klemeš, Jianqin Zheng, 2022, Energy.

Review on intelligent pipeline technologies: A life cycle perspective

H. Zhang, Jianqin Zheng, Yongtu Liang, 2023, Comput. Chem. Eng..

A two-stage improved genetic algorithm-particle swarm optimization algorithm for optimizing the pressurization scheme of coal bed methane gathering networks

Bohong Wang, Yongtu Liang, Haoran Zhang, 2019, Journal of Cleaner Production.

Deeppipe: A semi-supervised learning for operating condition recognition of multi-product pipelines

Yongtu Liang, Zhengbing Li, Jianqin Zheng, 2021 .

A point prediction method based automatic machine learning for day-ahead power output of multi-region photovoltaic plants

Yongtu Liang, Jianqin Zheng, Wenlong Shang, 2021 .

How government policies can make waste cooking oil-to-biodiesel supply chains more efficient and sustainable

M. Rajaeifar, Jianqin Zheng, Yongtu Liang, 2020 .

A hybrid framework for forecasting power generation of multiple renewable energy sources

J. Klemeš, Jianqin Zheng, Yongtu Liang, 2023, Renewable and Sustainable Energy Reviews.

Optimal Design of Energy System Based on the Forecasting Data with Particle Swarm Optimization

Yamin Yan, Jianqin Zheng, Liang Yongtu, 2020 .

Lightning Strike Location Identification Based on 3D Weather Radar Data

Manzhu Yu, Mingyue Lu, Jianqin Zheng, 2021, Frontiers in Environmental Science.

A methodology to restructure a pipeline system for an oilfield in the mid to late stages of development

Haoran Zhang, Yongtu Liang, Meng Yuan, 2018, Comput. Chem. Eng..

Robust Optimization for Emergency Scheduling of Oil Products After Disaster

Yongtu Liang, Qi Liao, Xiaodan Shi, 2019, IEEE Access.

Deeppipe: Theory-guided prediction method based automatic machine learning for maximum pitting corrosion depth of oil and gas pipeline

H. Zhang, Jianqin Zheng, Yongtu Liang, 2023, Chemical Engineering Science.

Deeppipe: Theory-guided LSTM method for monitoring pressure after multi-product pipeline shutdown

Yongtu Liang, Jianqin Zheng, Qi Liao, 2021, Process Safety and Environmental Protection.

A voyage with minimal fuel consumption for cruise ships

Yongtu Liang, Zhengbing Li, Bohong Wang, 2019, Journal of Cleaner Production.

An MILP model for the reformation of natural gas pipeline networks with hydrogen injection

Haoran Zhang, Bohong Wang, Meng Yuan, 2018, International Journal of Hydrogen Energy.

A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants

Jianqin Zheng, Yongtu Liang, Jiangshan Du, 2023, Eng. Appl. Artif. Intell..

Deeppipe: A hybrid model for multi-product pipeline condition recognition based on process and data coupling

Jianqin Zheng, Yongtu Liang, Qi Liao, 2022, Comput. Chem. Eng..

Deeppipe: Operating Condition Recognition of Multiproduct Pipeline Based on KPCA-CNN

Jianqin Zheng, Yongtu Liang, Qi Liao, 2022, Journal of Pipeline Systems Engineering and Practice.

Deeppipe: A hybrid intelligent framework for real-time batch tracking of multi-product pipelines

Jianqin Zheng, Yongtu Liang, Jiangshan Du, 2022, Chemical Engineering Research and Design.

Deeppipe: A deep-learning method for anomaly detection of multi-product pipelines

Jianqin Zheng, Yongtu Liang, Qi Liao, 2022, Energy.

Deeppipe: a customized generative model for estimations of liquid pipeline leakage parameters

Yongtu Liang, Taicheng Zheng, Zhengbing Li, 2021, Comput. Chem. Eng..

An online real-time estimation tool of leakage parameters for hazardous liquid pipelines

Yongtu Liang, Haoran Zhang, Jianqin Zheng, 2020, Int. J. Crit. Infrastructure Prot..

MaaS in Bike-Sharing: Smart Phone GPS Data Based Layout Optimization and Emission Reduction Potential Analysis

Ryosuke Shibasaki, Tianqi Xia, Haoran Zhang, 2018, Energy Procedia.

PM2.5 Concentration Forecasting over the Central Area of the Yangtze River Delta Based on Deep Learning Considering the Spatial Diffusion Process

Manzhu Yu, Jianqin Zheng, Mingyue Lu, 2021, Remote. Sens..

Time series prediction for output of multi-region solar power plants

Bohong Wang, Yongtu Liang, Haoran Zhang, 2020 .

Deeppipe: An intelligent framework for predicting mixed oil concentration of multi-product pipeline

Jianqin Zheng, Yongtu Liang, Jiangshan Du, 2023, Energy.

A risk assessment based optimization method for route selection of hazardous liquid railway network

Bohong Wang, Yongtu Liang, Meng Yuan, 2018, Safety Science.

A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction

J. Klemeš, Jianqin Zheng, Yongtu Liang, 2022, Energy.

Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis

Ryosuke Shibasaki, Tianqi Xia, Yin Long, 2019, Applied Energy.

A deep learning-based approach for predicting oil production: A case study in the United States

Yunlu Ma, Jianqin Zheng, Yongtu Liang, 2023, Energy.