A hybrid model approach for forecasting future residential electricity consumption
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Bing Dong | S. M. Mahbobur Rahman | Zhaoxuan Li | Rolando E. Vega | B. Dong | Zhaoxuan Li | S. Rahman | R. Vega | S.M. Mahbobur Rahman
[1] D.J. Leith,et al. Gaussian process prior models for electrical load forecasting , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.
[2] Abhishek Srivastav,et al. Integrated energy performance modeling for a retail store building , 2013 .
[3] Kevin M. Smith,et al. Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy , 2014 .
[4] Graeme Burt,et al. Enhanced Load Profiling for Residential Network Customers , 2014, IEEE Transactions on Power Delivery.
[5] Henrik Madsen,et al. Identification of the main thermal characteristics of building components using MATLAB , 2008 .
[6] James E. Braun,et al. An Inverse Gray-Box Model for Transient Building Load Prediction , 2002 .
[7] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[8] Abhishek Srivastav,et al. Baseline building energy modeling and localized uncertainty quantification using Gaussian mixture models , 2013 .
[9] Merih Aydinalp,et al. Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks , 2004 .
[10] Sylvain Calino,et al. Robot programming by demonstration : a probabilistic approach , 2009 .
[11] Qian Ding,et al. Application of LS-SVM in the Short-term Power Load Forecasting Based on QPSO , 2014 .
[12] Xindong Wu,et al. The Top Ten Algorithms in Data Mining , 2009 .
[13] M. Etezadi-Amoli,et al. Smart meter based short-term load forecasting for residential customers , 2011, 2011 North American Power Symposium.
[14] H. Mori,et al. Probabilistic short-term load forecasting with Gaussian processes , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.
[15] Tony N.T. Lam,et al. Artificial neural networks for energy analysis of office buildings with daylighting , 2010 .
[16] Lino Guzzella,et al. EKF based self-adaptive thermal model for a passive house , 2014 .
[17] Jin Yang,et al. On-line building energy prediction using adaptive artificial neural networks , 2005 .
[18] Eric Monmasson,et al. Thermal parameter identification of simplified building model with electric appliance , 2011, 11th International Conference on Electrical Power Quality and Utilisation.
[19] Philip Haves,et al. A Modular Building Controls Virtual Test Bed for the Integrations of Heterogeneous Systems , 2008 .
[20] Lynne E. Parker,et al. Predicting future hourly residential electrical consumption: A machine learning case study , 2012 .
[21] Refrigerating. ASHRAE handbook of fundamentals , 1967 .
[22] Jesús M. Zamarreño,et al. Prediction of hourly energy consumption in buildings based on a feedback artificial neural network , 2005 .
[23] Xinhua Xu,et al. A grey‐box model of next‐day building thermal load prediction for energy‐efficient control , 2008 .
[24] S. Fan,et al. Short-term load forecasting based on an adaptive hybrid method , 2006, IEEE Transactions on Power Systems.
[25] Mohammad Yusri Hassan,et al. A review on applications of ANN and SVM for building electrical energy consumption forecasting , 2014 .
[26] Abdullatif Ben-Nakhi,et al. Cooling load prediction for buildings using general regression neural networks , 2004 .
[27] Xueming Yang,et al. Comparison of the LS-SVM based load forecasting models , 2011, Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology.
[28] Guido Smits,et al. Improved SVM regression using mixtures of kernels , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[29] Yu Erkeng,et al. Short-term electrical load forecasting using least squares support vector machines , 2002, Proceedings. International Conference on Power System Technology.
[30] Zheng O'Neill,et al. TESTING AND VALIDATING AN EQUATION-BASED DYNAMIC BUILDING PROGRAM WITH ASHRAE STANDARD METHOD OF TEST , 2008 .
[31] Prashant G. Mehta,et al. Structure-preserving model reduction of nonlinear building thermal models , 2014, Autom..
[32] Benedikt Gregor Eric Schenker,et al. Prediction and control using feedback neural networks and partial models , 1996 .
[33] Victor M. Zavala,et al. On-line economic optimization of energy systems using weather forecast information. , 2009 .
[34] Desheng Dash Wu,et al. Power load forecasting using support vector machine and ant colony optimization , 2010, Expert Syst. Appl..
[35] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[36] Christian Ghiaus,et al. Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part I – Building modeling , 2012 .
[37] Bing Dong,et al. An investigation on energy-related occupancy behavior for low-income residential buildings , 2015 .
[38] Kenneth Levenberg. A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .
[39] Ali Azadeh,et al. Annual electricity consumption forecasting by neural network in high energy consuming industrial sectors , 2008 .
[40] Stéphane Bertagnolio,et al. Building and HVAC system simulation with the help of an engineering equation solver , 2008 .
[41] Yasuhiro Hayashi,et al. A Versatile Clustering Method for Electricity Consumption Pattern Analysis in Households , 2013, IEEE Transactions on Smart Grid.
[42] Johan A. K. Suykens,et al. Fixed-size Least Squares Support Vector Machines: A Large Scale Application in Electrical Load Forecasting , 2006, Comput. Manag. Sci..
[43] Zheng O'Neill,et al. MODEL-BASED THERMAL LOAD ESTIMATION IN BUILDINGS , 2010 .
[44] James E. Braun,et al. Evaluating the Performance of Building Thermal Mass Control Strategies , 2001 .