Validation and forecasting accuracy in models of climate change
R. Fildes and N. Kourentzes, 2011, International Journal of Forecasting, 27: 968-995. http://dx.doi.org/10.1016/j.ijforecast.2011.03.008
Modelling functional outliers for high frequency time series forecasting with neural networks: an empirical evaluation for electricity load data
N. Kourentzes, 2011, International Conference on Data Mining, DMIN’2011, Las Vegas, 18-21 July 2011.
Segmenting electrical load time series for forecasting? An empirical evaluation of daily UK load patterns
S. F. Crone and N. Kourentzes, 2011, International Joint Conference on Neural Networks, San Jose, 31-05 August 2011.
Semi-supervised monitoring of electric load time series for unusual patterns
N. Kourentzes and S. F. Crone, 2011, International Joint Conference on Neural Networks, San Jose, 31-05 August 2011.
Feature selection for time series prediction – A combined filter and wrapper approach for neural networks
S. F. Crone and N. Kourentzes, 2010, Neurocomputing, 73: 1923-1936. http://dx.doi.org/10.1016/j.neucom.2010.01.017
A neural network methodology for forecasting constant and dynamic demand rate for intermittent demand time series
N. Kourentzes and S. F. Crone, 2010, The 30th Annual international Symposium on Forecasting, San Diego.
Inference for Neural Network Predictive Models with Impulse Interventions
N. Kourentzes and S. F. Crone, 2010, Proceedings of the 2010 International Conference on Data Mining, DMIN’10, Las Vegas, USA, CSREA.
Frequency independent automatic input variable selection for neural networks for forecasting
N. Kourentzes and S. F. Crone, 2010, International Joint Conference on Neural Networks, Barcelona Spain, 18-23 July 2010.
Evaluation of input variable selection methodologies for multilayer perceptrons for high frequency time series
N. Kourentzes and S. F. Crone, 2009, The 29th Annual international Symposium on Forecasting, Hong Kong.
Input-variable specification for neural networks – an analysis of forecasting low and high time series frequency
S. F. Crone and N. Kourentzes, 2009, IJCNN’09, Atlanta, USA, IEEE: New York, pp. 3221-3228.