Comparison of artificial intelligence methods for predicting the time series problem

Authors:
S. Sp. Pappas;L. Ekonomou
Affiliations:
University of the Aegean, Information & Communications Systems Engineering, Athens, Greece;Public Power Corporation S.A., Athens, Greece
Venue:
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Year:
2006

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Abstract

This paper studies the time series prediction problem. Artificial intelligence methods are applied to two different time series in order to compare their effectiveness and their producing results. The applied methods are based on the Group Method of Data Handling (GMDH) algorithms and the hybrid method of GMDH and Genetic Algorithms, i.e. Genetics-Based Self-Organising Network (GBSON). Finally useful conclusions and the advantages and disadvantages of each method are stated.