Data analytics for simplifying thermal efficiency planning in cities
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Franz-Josef Ulm | Joseph Ferreira | Marta C. González | Mohammad Javad Abdolhosseini Qomi | Arash Noshadravan | Jake M Sobstyl | Jameson Toole | Roland J-M Pellenq | Marta C Gonzalez | Jameson L. Toole | F. Ulm | R. Pellenq | J. Ferreira | J. M. Sobstyl | A. Noshadravan | M. J. Abdolhosseini Qomi
[1] Lee S. Smith,et al. An Explanation , 1889, The American journal of dental science.
[2] Moshe Ben-Akiva,et al. Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .
[3] Heather Cruickshank,et al. Closing the Energy Efficiency Gap: A study linking demographics with barriers to adopting energy efficiency measures in the home , 2012 .
[4] P. Berkhout,et al. Defining the rebound effect , 2000 .
[5] Reinhard Haas,et al. The rebound effect for space heating Empirical evidence from Austria , 2000 .
[6] J. Friedman. Multivariate adaptive regression splines , 1990 .
[7] V. Ismet Ugursal,et al. Modeling of end-use energy consumption in the residential sector: A review of modeling techniques , 2009 .
[8] Jiejin Cai,et al. Applying support vector machine to predict hourly cooling load in the building , 2009 .
[9] D. Claridge,et al. A Fourier Series Model to Predict Hourly Heating and Cooling Energy Use in Commercial Buildings With Outdoor Temperature as the Only Weather Variable , 1999 .
[10] L. Brand. The Pi theorem of dimensional analysis , 1957 .
[11] Moncef Krarti,et al. Building Energy Use Prediction and System Identification Using Recurrent Neural Networks , 1995 .
[12] Margaret F. Fels,et al. Refraction of PRISM results into components of saved energy , 1986 .
[13] Dejan Mumovic,et al. A review of bottom-up building stock models for energy consumption in the residential sector , 2010 .
[14] Anne Grete Hestnes,et al. Energy use in the life cycle of conventional and low-energy buildings: A review article , 2007 .
[15] Olivier L. de Weck,et al. Isoperformance: Analysis and design of complex systems with desired outcomes , 2006 .
[16] Robert G. Quayle,et al. Heating Degree Day Data Applied to Residential Heating Energy Consumption , 1980 .
[17] Zheng O'Neill,et al. Uncertainty and sensitivity decomposition of building energy models , 2012 .
[18] K. V. Van Vliet,et al. Combinatorial molecular optimization of cement hydrates , 2014, Nature Communications.
[19] Margaret F. Fels. PRISM: An Introduction , 1986 .
[20] Massimiliano Manfren,et al. Calibration and uncertainty analysis for computer models – A meta-model based approach for integrated building energy simulation , 2013 .
[21] X. Gabaix. Zipf's Law for Cities: An Explanation , 1999 .
[22] John R. Anderson,et al. MACHINE LEARNING An Artificial Intelligence Approach , 2009 .
[23] L. Bettencourt,et al. A unified theory of urban living , 2010, Nature.
[24] Christoph F. Reinhart,et al. The simulation of annual daylight illuminance distributions — a state-of-the-art comparison of six RADIANCE-based methods , 2000 .
[25] Mark E. J. Newman,et al. Power-Law Distributions in Empirical Data , 2007, SIAM Rev..
[26] Dwight M. Jaffee,et al. Energy efficiency retrofits for U.S. housing: Removing the bottlenecks , 2014 .
[27] Roland J.-M. Pellenq,et al. Physical Origins of Thermal Properties of Cement Paste , 2015 .
[28] Y. Shimoda,et al. Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model , 2007 .
[29] Abdolhosseini Qomi,et al. From atoms to cities : A bottom-up analysis of infrastructure materials and systems , 2015 .
[30] D. Sailor,et al. Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states , 1997 .
[31] H. Haeri,et al. Economic efficiency v energy efficiency : Do model conservation standards make good sense? , 1990 .
[32] L. Kilian. The Economic Effects of Energy Price Shocks , 2007 .
[33] Jlm Jan Hensen,et al. Uncertainty analysis in building performance simulation for design support , 2011 .
[34] Pieter de Wilde,et al. Identification of key factors for uncertainty in the prediction of the thermal performance of an office building under climate change , 2009 .
[35] Marshall B. Jones,et al. Isoperformance: Analysis and design of complex systems with desired outcomes , 2006, Syst. Eng..
[36] Daniel E. Fisher,et al. EnergyPlus: creating a new-generation building energy simulation program , 2001 .
[37] Stefano Tarantola,et al. Application of global sensitivity analysis of model output to building thermal simulations , 2008 .
[38] Frédéric Magoulès,et al. A review on the prediction of building energy consumption , 2012 .
[39] Jesús M. Zamarreño,et al. Prediction of hourly energy consumption in buildings based on a feedback artificial neural network , 2005 .
[40] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[41] Franco Chingcuanco,et al. A microsimulation model of urban energy use: Modelling residential space heating demand in ILUTE , 2012, Comput. Environ. Urban Syst..
[42] Wei Tian,et al. A review of sensitivity analysis methods in building energy analysis , 2013 .
[43] Saltelli Andrea,et al. Global Sensitivity Analysis: The Primer , 2008 .
[44] J. Zico Kolter,et al. A Large-Scale Study on Predicting and Contextualizing Building Energy Usage , 2011, AAAI.