Optimizing legacy building operation: The evolution into data-driven predictive cyber-physical systems
暂无分享,去创建一个
Mischa Schmidt | Karel Macek | Anett Schulke | Karel Mařík | M. Victoria Moreno | Alfonso Gordaliza Pastor | K. Macek | M. Moreno | K. Marik | A. Schulke | Mischa Schmidt | Alfonso Gordaliza Pastor
[1] José L. Hernández,et al. A novel middleware for smart grid data exchange towards the energy efficiency in buildings , 2015, 2015 International Conference and Workshops on Networked Systems (NetSys).
[2] P. O. Fanger,et al. Thermal comfort: analysis and applications in environmental engineering, , 1972 .
[3] Guofei Jiang,et al. Modeling and analytics for cyber-physical systems in the age of big data , 2014, PERV.
[4] Andrew Kusiak,et al. Multi-objective optimization of the HVAC (heating, ventilation, and air conditioning) system performance , 2015 .
[5] Lars Junghans,et al. Hybrid single objective genetic algorithm coupled with the simulated annealing optimization method for building optimization , 2015 .
[6] Farrokh Janabi-Sharifi,et al. Black-box modeling of residential HVAC system and comparison of gray-box and black-box modeling methods , 2015 .
[7] Teresa Wu,et al. Short-term building energy model recommendation system: A meta-learning approach , 2016 .
[8] Li Xia,et al. Satisfaction based Q-learning for integrated lighting and blind control , 2016 .
[9] R. Belmans,et al. Reinforcement Learning Applied to an Electric Water Heater: From Theory to Practice , 2015, IEEE Transactions on Smart Grid.
[10] Dimitrios V. Rovas,et al. Holistic optimization of HVAC systems via distributed data-driven control , 2014, ICIS 2014.
[11] Yacine Rezgui,et al. An ANN-GA Semantic Rule-Based System to Reduce the Gap Between Predicted and Actual Energy Consumption in Buildings , 2017, IEEE Transactions on Automation Science and Engineering.
[12] Dennis Weyland,et al. A critical analysis of the harmony search algorithm—How not to solve sudoku , 2015 .
[13] Yudong Zhang,et al. A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications , 2015 .
[14] Xin-She Yang,et al. Nature-Inspired Metaheuristic Algorithms , 2008 .
[15] Mischa Schmidt,et al. The energy efficiency problematics in sports facilities: identifying savings in daily grass heating operation , 2015, ICCPS.
[16] Samrat L. Sabat,et al. Optimal chiller loading for energy conservation using a new differential cuckoo search approach , 2014 .
[17] Hermann Merz,et al. Building Automation: Communication systems with EIB/KNX, LON and BACnet , 2009 .
[18] Nursyarizal Mohd Nor,et al. A review on optimized control systems for building energy and comfort management of smart sustainable buildings , 2014 .
[19] S. Mahadevan,et al. A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy , 2015 .
[20] Lei Yang,et al. Reinforcement learning for optimal control of low exergy buildings , 2015 .
[21] Zhengwei Li,et al. Using Support Vector Machine to Predict Next Day Electricity Load of Public Buildings with Sub-metering Devices☆ , 2015 .
[22] Antonio F. Gómez-Skarmeta,et al. Context sensitive indoor temperature forecast for energy efficient operation of smart buildings , 2015, 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT).
[23] António E. Ruano,et al. The IMBPC HVAC system: A complete MBPC solution for existing HVAC systems , 2016 .
[24] Edward A. Lee,et al. A model-based design methodology for cyber-physical systems , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.
[25] Karel Mařík,et al. A methodology for quantitative comparison of control solutions and its application to HVAC (heating, ventilation and air conditioning) systems , 2012 .
[26] Francesco Borrelli,et al. Predictive Control for Energy Efficient Buildings with Thermal Storage: Modeling, Stimulation, and Experiments , 2012, IEEE Control Systems.
[27] Giuseppe Tommaso Costanzo,et al. Experimental analysis of data-driven control for a building heating system , 2015, ArXiv.
[28] Bernhard Rumpe,et al. Modeling cyber-physical systems: model-driven specification of energy efficient buildings , 2012, MOTPW '12.
[29] Francesco Massa Gray,et al. Thermal building modelling using Gaussian processes , 2016 .
[30] Martin T. Hagan,et al. Gauss-Newton approximation to Bayesian learning , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).
[31] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[32] Bart De Schutter,et al. Reinforcement Learning and Dynamic Programming Using Function Approximators , 2010 .
[33] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[34] Gerardo Maria Mauro,et al. Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort , 2016 .
[35] Young Jin Kim,et al. BIM interface for full vs. semi-automated building energy simulation , 2014 .
[36] Xin-She Yang,et al. Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).
[37] Andrew Kusiak,et al. Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms , 2015 .
[38] Viviana Cocco Mariani,et al. Improved firefly algorithm approach applied to chiller loading for energy conservation , 2013 .
[39] T. M. Leung,et al. A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings , 2015 .