Time series: Empirical characterization and artificial neural network-based selection of forecasting techniques

Abstract

In this work a method to facilitate the elaboration of a forecast for people with little statistical training is proposed. The method uses a rather simple yet sufficiently accurate time series characterization that allowed training a series of artificial neural networks (ANNs) to predict the forecasting performance of several statistical techniques. A case study is presented to demonstrate the application of the method. All techniques used, including the ANN, were conveniently coded in MS Excel so the computational requirements are modest. Furthermore, the results can be tabulated for quick consultation.

DOI: 10.3233/IDA-2009-0403

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Cite this paper

@article{Marroqun2009TimeSE, title={Time series: Empirical characterization and artificial neural network-based selection of forecasting techniques}, author={Mar{\'i}a Guadalupe Villarreal Marroqu{\'i}n and Mary Carmen Acosta Cervantes and Jos{\'e} Luis Mart{\'i}nez Flores and Mauricio Cabrera-R{\'i}os}, journal={Intell. Data Anal.}, year={2009}, volume={13}, pages={969-982} }