Diagnostic tools of energy performance for supermarkets using Artificial Neural Network algorithms
暂无分享,去创建一个
[1] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[2] L. S. Moulin,et al. Confidence intervals for neural network based short-term load forecasting , 2000 .
[3] R. Hecht-Nielsen. Kolmogorov''s Mapping Neural Network Existence Theorem , 1987 .
[4] D. Marquardt. An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .
[5] Jin Yang,et al. On-line building energy prediction using adaptive artificial neural networks , 2005 .
[6] Soteris A. Kalogirou,et al. Applications of artificial neural networks in energy systems , 1999 .
[7] Soteris A. Kalogirou,et al. Artificial neural networks in energy applications in buildings , 2006 .
[8] Georgios A. Florides,et al. Development of a Neural Network-Based Fault Diagnostic System , 2006 .
[9] Rosdiazli Ibrahim,et al. Development of Neural Network Prediction Model of Energy Consumption , 2011 .
[10] Demetris Stathakis,et al. How many hidden layers and nodes? , 2009 .
[11] Lasse Rosendahl,et al. Methods to improve prediction performance of ANN models , 2003, Simul. Model. Pract. Theory.
[12] Martin Hrncar,et al. Performance monitoring strategies for effective running of commercial refrigeration systems , 2010 .
[13] V. Vemuri,et al. Artificial neural networks: an introduction , 1988 .
[14] S. Tassou,et al. Application of Neural Networks for the Prediction of the Energy Consumption in a Supermarket , 2005 .
[15] Thomas Olofsson,et al. A method for predicting the annual building heating demand based on limited performance data , 1998 .
[16] Petr Stluka,et al. Performance Monitoring of the Refrigeration System with Minimum Set of Sensors , 2012 .
[17] Alberto Hernandez Neto,et al. Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption , 2008 .
[18] Richard Watkins,et al. Potential for Solar Energy in Food Manufacturing, Distribution and Retail , 2007 .
[19] Soteris A. Kalogirou,et al. MODELING OF SOLAR DOMESTIC WATER HEATING SYSTEMS USING ARTIFICIAL NEURAL NETWORKS , 1999 .
[20] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.
[21] Carlos E. Pedreira,et al. Neural networks for short-term load forecasting: a review and evaluation , 2001 .
[22] Melek Yalcintas,et al. Energy-savings predictions for building-equipment retrofits , 2008 .
[23] Duan Li,et al. On Restart Procedures for the Conjugate Gradient Method , 2004, Numerical Algorithms.
[24] M. Mohanraj,et al. Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review , 2012, Renewable and Sustainable Energy Reviews.
[25] P. S. Szczepaniak. Application of neural networks for fault diagnosis in a power plant , 1994 .
[26] Savvas A. Tassou,et al. Artificial neural network based electrical load prediction for food retail stores , 1998 .
[27] Savvas A. Tassou,et al. Reduction of refrigeration energy consumption and environmental impacts in food retailing. , 2008 .
[28] Kenneth Levenberg. A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .
[29] G. Florides,et al. Development of a neural network-based fault diagnostic system for solar thermal applications , 2008 .
[30] Domingo Docampo,et al. Neural networks in fault detection: a case study , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).
[31] Timothy Masters,et al. Neural, Novel & Hybrid Algorithms for Time Series Prediction , 1995 .
[32] Tatsushi Nishi,et al. Application of Neural Network to Fault Diagnosis ofElectro-Mechanical System , 2005 .
[33] Jan F. Kreider,et al. The design and viability of a probabilistic fault detection and diagnosis method for vapor compression cycle equipment , 1998 .
[34] Simon Haykin,et al. Neural Networks and Learning Machines , 2010 .
[35] Jesús M. Zamarreño,et al. Prediction of hourly energy consumption in buildings based on a feedback artificial neural network , 2005 .
[36] Soteris A. Kalogirou,et al. Artificial neural networks in renewable energy systems applications: a review , 2001 .
[37] T. Olofsson,et al. Long-term energy demand predictions based on short-term measured data , 2001 .
[38] John E. Dennis,et al. Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.
[39] Kenneth A. Loparo,et al. A neural-network approach to fault detection and diagnosis in industrial processes , 1997, IEEE Trans. Control. Syst. Technol..