Analyzing industrial energy use through ordinary least squares regression models
暂无分享,去创建一个
[1] J. S. Haberl,et al. Impact of using measured weather data vs. TMY weather data in a DOE-2 simulation , 1995 .
[2] David E. Claridge,et al. A development and comparison of NAC estimates for linear and change-point energy models for commercial buildings , 1993 .
[3] David E. Claridge,et al. Measuring energy-saving retrofits: Experiences from the Texas LoanSTAR program , 1996 .
[4] David J. C. MacKay,et al. BAYESIAN NON-LINEAR MODELING FOR THE PREDICTION COMPETITION , 1996 .
[5] David E. Claridge. A Perspective on Methods for Analysis of Measured Energy Data from Commercial Buildings , 1998 .
[6] J. Kelly Kissock,et al. Measuring industrial energy savings , 2008 .
[7] Steven C. Chapra,et al. Applied Numerical Methods with MATLAB for Engineers and Scientists , 2004 .
[8] Tao Hong,et al. Modeling and forecasting hourly electric load by multiple linear regression with interactions , 2010, IEEE PES General Meeting.
[9] David E. Claridge,et al. A Four-Parameter Change-Point Model for Predicting Energy Consumption in Commercial Buildings , 1992 .
[10] Carl Eger. Integrating methods of statistical analysis to identify energy‐saving opportunities , 2006 .
[11] Margaret F. Fels. PRISM: An Introduction , 1986 .
[12] Jeffrey S. Simonoff,et al. Handbook of Regression Analysis , 2012 .
[13] B. P. Feuston,et al. Generalized nonlinear regression with ensemble of neural nets: The great energy predictor shootout , 1994 .
[14] N. Draper,et al. Applied Regression Analysis , 1966 .
[15] Helge Toutenburg,et al. Linear models : least squares and alternatives , 1999 .
[16] Carsten Peterson,et al. Predicting System loads with Artificial Neural Networks : Method and Result from "the Great Energy Predictor Shootout" , 1994 .
[17] David E. Claridge,et al. A Change-Point Principal Component Analysis (CP/PCA) Method for Predicting Energy Usage in Commercial Buildings: The PCA Model , 1993 .
[18] John Seryak,et al. UNDERSTANDING MANUFACTURING ENERGY USE THROUGH STATISTICAL ANALYSIS , 2004 .
[19] J. K. Kissock. A Methodology to Measure Retrofit Energy Savings in Commercial Buildings , 2008 .
[20] Dan Brown,et al. Estimating Industrial Building Energy Savings using Inverse Simulation , 2011 .
[21] T. Agami Reddy,et al. Applied Data Analysis and Modeling for Energy Engineers and Scientists , 2011 .
[22] David E. Claridge,et al. Bias in Predicting Annual Energy Use in Commercial Buildings with Regression Models Developed from Short Data Sets , 1994 .
[23] David E. Claridge,et al. Inverse Modeling Toolkit: Numerical Algorithms for Best-Fit Variable-Base Degree Day and Change Point Models , 2003 .
[24] David E. Claridge,et al. Multivariate Regression Modeling , 1998 .
[25] A. Rabl,et al. Energy signature models for commercial buildings: test with measured data and interpretation , 1992 .
[26] Sedat Akkurt,et al. Artificial neural networks applications in building energy predictions and a case study for tropical climates , 2005 .
[27] David E. Claridge,et al. An Overview of Measured Energy Retrofit Savings Methodologies Developed in the Texas LoanSTAR Program , 1994 .
[28] J. F. Kreider,et al. Neural networks applied to buildings -- A tutorial and case studies in prediction and adaptive control , 1996 .
[29] Dale Borowiak,et al. Linear Models, Least Squares and Alternatives , 2001, Technometrics.
[30] H. Akbari,et al. Application of an End-Use Disaggregation Algorithm for Obtaining Building Energy-Use Data , 1998 .
[31] T. A. Reddy,et al. Uncertainty in baseline regression modeling and in determination of retrofit savings , 1998 .
[32] David E. Claridge,et al. Ambient-temperature regression analysis for estimating retrofit savings in commercial buildings , 1998 .
[33] Leon S. Lasdon,et al. Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming , 1978, TOMS.
[34] V. Geros,et al. Modeling and predicting building's energy use with artificial neural networks: Methods and results , 2006 .
[35] David E. Claridge,et al. Baselining methodology for facility-level monthly energy use. Part 1: Theoretical aspects , 1997 .
[36] Wayne Turner,et al. Energy Management Handbook , 2020 .
[37] Lawrence C. Marsh. Spline Regression Models , 2001 .
[38] Robert C. Sonderegger,et al. A Baseline Model for Utility Bill Analysis Using Both Weather and Non-Weather Related Variables 1 , 1998 .
[39] David E. Claridge,et al. Inverse Modeling Toolkit: Numerical Algorithms , 2004 .
[40] David E. Claridge,et al. Development of a Toolkit for Calculating Linear, Change–Point Linear and Multiple–Linear Inverse Building Energy Analysis Models, ASHRAE Research Project 1050-RP, Detailed Test Results , 2001 .
[41] Leon S. Lasdon,et al. Design and Use of the Microsoft Excel Solver , 1998, Interfaces.
[42] Kelly Kissock,et al. Understanding Industrial Energy Use through Sliding Regression Analysis , 2007 .
[43] David E. Claridge,et al. Baselining methodology for facility-level monthly energy use - Part 2: application to eight army installations , 1997 .
[44] David E. Claridge,et al. Use of Simplified System Models to Measure Retrofit Energy Savings , 1993 .
[45] Carlos Gershenson,et al. Artificial Neural Networks for Beginners , 2003, ArXiv.
[46] John Kissock,et al. Modeling commercial building energy use with artificial neural networks , 1994 .
[47] Moncef Krarti,et al. Estimation of energy savings for building retrofits using neural networks , 1998 .
[48] David E. Claridge,et al. Baseline calculations for measurement and verification of energy and demand savings in a revolving loan program in Texas , 1998 .
[49] Jay L. Devore,et al. Probability and statistics for engineering and the sciences , 1982 .
[50] David E. Claridge,et al. Predicting Energy Usage in a Supermarket , 1989 .