A5102003690- Hydraulic Fracturing and Reservoir Analysis
- Soil, Finite Element Methods
- Seismic Imaging and Inversion Techniques
- Underground infrastructure and sustainability
- Civil and Geotechnical Engineering Research
- Drilling and Well Engineering
- Advanced Vision and Imaging
- Geomechanics and Mining Engineering
- Advanced Battery Technologies Research
- Plant nutrient uptake and metabolism
- Electric and Hybrid Vehicle Technologies
- Geotechnical Engineering and Soil Stabilization
- Video Surveillance and Tracking Methods
- Electric Vehicles and Infrastructure
- Smart Grid Energy Management
- Geoscience and Mining Technology
- Refrigeration and Air Conditioning Technologies
- Building Energy and Comfort Optimization
- Advanced Measurement and Detection Methods
- Irrigation Practices and Water Management
- Reservoir Engineering and Simulation Methods
- Soil Carbon and Nitrogen Dynamics
Sun Yat-sen University
2023-2024
China University of Petroleum, East China
2023
Northwest A&F University
2020
Research Institute of Petroleum Exploration and Development
2013
BGC Engineering (Canada)
2007
Heating, ventilation, and air conditioning (HVAC) energy consumption now accounts for a major portion of use buildings. Therefore, finding the optimal energy-saving control strategy HVAC systems to optimize has become crucial in realizing savings, emission reductions, green Traditional methods parameter require complex physical model calculation; continuous coupled parameters are handled poorly. Developing deep reinforcement learning (DRL) provides new ideas optimization. Herein, DRL-based...
Abstract Field experiences suggest significant interaction between natural fractures and hydraulic in unconventional reservoir some tight gas sandstone. Microseismic monitoring is a widely used methodology to understand the real-time evolution of fracture geometry during fracturing, which essential for evaluating SRV under certain treatment, especially reservoir. Howerver, correlation real microseismic results still open discuss. Therefore, understanding relationships induced acoustic...
In this work, two reinforcement-learning-based energy management strategies are investigated for plug-in hybrid electric vehicles (PHEVs). The developed based on the Toyota Prius model, which dynamics firstly established. Then, both deep Q-learning (DQN) and deterministic policy gradient (DDPG) algorithms formulated vehicle model. Furthermore, to verify effectiveness, also benchmarked against dynamic programming under New European Driving Cycle (NEDC). simulation results indicate that DQN...
Abstract Unmanned aerial vehicles (UAVs) and Ground Vehicles (UGVs) are widely used in various fields, autonomous tracking of UGV by UAV can significantly improve the collaborative capability operational range unmanned systems. In order to realize complex cluttered scenarios, this paper presents a vision‐based system for UGV, integrating visual target model based on deep learning with local path planning methodology. The includes learning‐based tracker, state machine, an obstacle avoidance...