Sample data selection method for improving the prediction accuracy of the heating energy consumption

This publication has 41 references indexed in Scilit:

• Evaluation of a multiple linear regression model and SARIMA model in forecasting heat demand for district heating system
  Applied Energy, 2016
• Prediction of time series of NPP operating parameters using dynamic model based on BP neural network
  Annals of Nuclear Energy, 2015
• A new strategy to prevent over-fitting in partial least squares models based on model population analysis
  Analytica Chimica Acta, 2015
• A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network
  Applied Energy, 2014
• Sample size determination for logistic regression
  Journal of Computational and Applied Mathematics, 2014
• The prediction of heating energy consumption in a model house by using artificial neural networks in Denizli–Turkey
  Advances in Engineering Software, 2010
• Investigation of some large building energy conservation opportunities using the doe-2 model
  Energy Conversion and Management, 1999
• Incorporating prior information in machine learning by creating virtual examples
  Proceedings of the IEEE, 1998
• Describing the uncertainties in experimental results
  Experimental Thermal and Fluid Science, 1988
• A Mathematical Theory of Communication
  Bell System Technical Journal, 1948