His main research concerns Simulation, Efficient energy use, Control engineering, Fault detection and isolation and Optimal control. His biological study spans a wide range of topics, including Energy performance, Airflow, Air conditioning, Demand controlled ventilation and Ventilation. His Efficient energy use research is multidisciplinary, incorporating elements of Architectural engineering, Occupancy, Humidity, Meteorology and Energy.
His study in Control engineering is interdisciplinary in nature, drawing from both Reliability, Demand response, Smart grid and Zero-energy building. His Fault detection and isolation research includes elements of Data mining, Chiller and Principal component analysis, Robustness, Artificial intelligence. His Optimal control research includes themes of Chilled water and Genetic algorithm.
His scientific interests lie mostly in Control engineering, Chiller, Simulation, Air conditioning and Efficient energy use. Shengwei Wang has included themes like Control system, Optimal control, Robustness, Control theory and Principal component analysis in his Control engineering study. His Optimal control research incorporates elements of Control, Genetic algorithm and Water cooling.
His Chiller study combines topics in areas such as Reliability engineering, Cooling load, Fault detection and isolation, Chilled water and Water chiller. Shengwei Wang has researched Simulation in several fields, including Airflow and Automotive engineering. The study incorporates disciplines such as Energy consumption, Energy performance and Thermal comfort in addition to Air conditioning.
His primary areas of study are Reliability engineering, Air conditioning, Automotive engineering, Optimal design and Efficient energy use. His Reliability engineering research incorporates themes from Chiller, Control, Probabilistic logic, Energy and Systems design. His work deals with themes such as Thermal comfort, Control engineering, Chilled water, Water chiller and Demand response, which intersect with Chiller.
His Air conditioning study integrates concerns from other disciplines, such as Uncertainty analysis and Equation of state. His study looks at the intersection of Automotive engineering and topics like Smart grid with Power, Game theory, Renewable energy and Peak demand. The various areas that Shengwei Wang examines in his Efficient energy use study include Data center, Process engineering and Cooling load.
Shengwei Wang spends much of his time researching Smart grid, Demand response, Air conditioning, Optimal design and Efficient energy use. The Smart grid study combines topics in areas such as Electricity, Game theory, Chiller and Operations research. Shengwei Wang interconnects Chilled water, Control engineering and Power in the investigation of issues within Chiller.
His biological study spans a wide range of topics, including Peak demand and Thermal energy storage. His research integrates issues of Energy consumption and Automotive engineering in his study of Air conditioning. His studies examine the connections between Thermal comfort and genetics, as well as such issues in Control system, with regards to Simulation.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A dynamic user authentication scheme for wireless sensor networks
K.H.M. Wong;Yuan Zheng;Jiannong Cao;Shengwei Wang.
sensor networks ubiquitous and trustworthy computing (2006)
Supervisory and optimal control of building HVAC systems: A review
Shengwei Wang;Zhenjun Ma.
Hvac&r Research (2008)
Intelligent building research: a review
J. K.W. Wong;Heng Li;Shengwei Wang.
Automation in Construction (2005)
Dynamic characteristics and energy performance of buildings using phase change materials: A review
Na Zhu;Zhenjun Ma;Shengwei Wang.
Energy Conversion and Management (2009)
Model-based optimal control of VAV air-conditioning system using genetic algorithm
Shengwei Wang;Xinqiao Jin.
Building and Environment (2000)
Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques
Cheng Fan;Fu Xiao;Shengwei Wang.
Applied Energy (2014)
Simplified building model for transient thermal performance estimation using GA-based parameter identification
Shengwei Wang;Xinhua Xu.
International Journal of Thermal Sciences (2006)
Quantitative energy performance assessment methods for existing buildings
Shengwei Wang;Chengchu Yan;Fu Xiao.
Energy and Buildings (2012)
AHU sensor fault diagnosis using principal component analysis method
Shengwei Wang;Fu Xiao.
Energy and Buildings (2004)
Intelligent Buildings and Building Automation
Shengwei Wang.
(2009)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
Hong Kong Polytechnic University
University of Wollongong
Beijing Institute of Technology
Hong Kong Polytechnic University
Technical University of Denmark
Hong Kong Polytechnic University
Georgia Institute of Technology
Tsinghua University
Hong Kong Polytechnic University
Indian Institute of Technology Delhi
École Polytechnique Fédérale de Lausanne
University of Sfax
Salk Institute for Biological Studies
University College Dublin
Vanderbilt University
University of Otago
Commonwealth Scientific and Industrial Research Organisation
University of Florida
Czech University of Life Sciences Prague
University of Virginia
Cedars-Sinai Medical Center
National Institutes of Health
The Ohio State University
Northwestern University
MLL Munich Leukemia Laboratory
University of Virginia