Title :
Time series prediction with ensemble models
Author :
Wichard, Jorg D. ; Ogorzalek, Maciej
Author_Institution :
Dept. of Electr. Eng., AGH Univ. of Sci. & Technol., Krakow, Poland
Abstract :
We describe the use of ensemble methods to build proper models for time series prediction. Our approach extends the classical ensemble methods for neural networks by using several different model architectures. We further suggest an iterated prediction procedure to select the final ensemble members.
Keywords :
learning (artificial intelligence); neural net architecture; pattern classification; prediction theory; time series; ensemble members selection; ensemble methods; iterated prediction method; neural network training; time series prediction models; Buildings; Cats; Fluctuations; Neural networks; Predictive models; Probability distribution; Regression tree analysis; Support vector machines;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380203
