Mathematical optimization, Lagrangian relaxation, Control theory, Scheduling and Dynamic programming are his primary areas of study. His Mathematical optimization study combines topics from a wide range of disciplines, such as Wind power, Probabilistic logic, Power system simulation and Job shop scheduling. His work carried out in the field of Lagrangian relaxation brings together such families of science as Lagrange multiplier, Schedule and Subgradient method.
As a part of the same scientific study, Xiaohong Guan usually deals with the Control theory, concentrating on Model predictive control and frequently concerns with Stochastic programming, Stochastic optimization, Battery energy storage, Salient and State space. The concepts of his Scheduling study are interwoven with issues in Time horizon and Fluid coupling. His Dynamic programming research is multidisciplinary, incorporating elements of Discretization and Operating cost.
Xiaohong Guan spends much of his time researching Mathematical optimization, Data mining, Artificial intelligence, Wind power and Real-time computing. His Mathematical optimization study integrates concerns from other disciplines, such as Scheduling and Power system simulation. His Data mining study combines topics in areas such as Sampling and Network security.
His studies deal with areas such as Machine learning, Authentication and Pattern recognition as well as Artificial intelligence. His Wind power research includes themes of Markov decision process and Renewable energy. Xiaohong Guan has researched Lagrangian relaxation in several fields, including Lagrange multiplier, Dynamic programming and Subgradient method.
His primary scientific interests are in Mathematical optimization, Data mining, Renewable energy, Computer security and Artificial intelligence. His study of Optimization problem is a part of Mathematical optimization. His Data mining research incorporates elements of Traffic classification, Flow network, Sampling, Ensemble learning and Statistical classification.
His study on Renewable energy also encompasses disciplines like
His scientific interests lie mostly in Computer security, The Internet, Social network, Automotive engineering and Energy. His study in Computer security is interdisciplinary in nature, drawing from both Camera placement and Smart grid. His Automotive engineering research incorporates elements of Wind power, Scalability, Heuristic, HVAC and Renewable energy.
His study explores the link between Scalability and topics such as Authentication protocol that cross with problems in Artificial intelligence and Machine learning. He combines subjects such as Energy consumption, Ventilation, Energy conservation and Cyber-physical system with his study of Energy. In his papers, Xiaohong Guan integrates diverse fields, such as Shortest path problem, Scheduling and Mathematical optimization.
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Energy-Efficient Buildings Facilitated by Microgrid
Xiaohong Guan;Zhanbo Xu;Qing-Shan Jia.
IEEE Transactions on Smart Grid (2010)
An optimization-based method for unit commitment
X. Guan;P.B. Luh;H. Yan;J.A. Amalfi.
International Journal of Electrical Power & Energy Systems (1992)
Coordinated Multi-Microgrids Optimal Control Algorithm for Smart Distribution Management System
Jiang Wu;Xiaohong Guan.
IEEE Transactions on Smart Grid (2013)
An SVM-based machine learning method for accurate internet traffic classification
Ruixi Yuan;Zhu Li;Xiaohong Guan;Li Xu.
Information Systems Frontiers (2010)
Nonlinear approximation method in Lagrangian relaxation-based algorithms for hydrothermal scheduling
Xiaohong Guan;P.B. Luh;Lan Zhang.
IEEE Transactions on Power Systems (1995)
Performance Analysis and Comparison on Energy Storage Devices for Smart Building Energy Management
Zhanbo Xu;Xiaohong Guan;Qing-Shan Jia;Jiang Wu.
IEEE Transactions on Smart Grid (2012)
Optimization based methods for unit commitment: Lagrangian relaxation versus general mixed integer programming
Xiaohong Guan;Qiaozhu Zhai;A. Papalexopoulos.
2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491) (2003)
Revenue adequate bidding strategies in competitive electricity markets
Chao-An Li;A.J. Svoboda;Xiaohong Guan;H. Singh.
IEEE Transactions on Power Systems (1999)
Forecasting power market clearing price and quantity using a neural network method
Feng Gao;Xiaohong Guan;Xi-Ren Cao;A. Papalexopoulos.
power engineering society summer meeting (2000)
Optimization-based scheduling of hydrothermal power systems with pumped-storage units
Xiaohong Guan;P.B. Luh;Houzhong Yen;P. Rogan.
IEEE Transactions on Power Systems (1994)
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