PSO based Neural Networks vs. traditional statistical models for seasonal time series forecasting

Seasonality is a distinctive characteristic which is often observed in many practical time series. Artificial Neural Networks (ANNs) are a class of promising models for efficiently recognizing and forecasting seasonal patterns. In this paper, the Particle Swarm Optimization (PSO) approach is used to...

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Bibliographische Detailangaben

Hauptverfasser:	Adhikari, R., Agrawal, R. K., Kant, L.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	ANN Artificial neural networks Box-Jenkins models Computational modeling Elman ANN Forecasting particle swarm optimization Predictive models seasonality Support vector machines Time series analysis time series forecasting Training
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