A COMPARISON OF VAR AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING PRICE OF OIL

Author(s):  
Sam Mirmirani ◽  
Hsi Cheng Li
2000 ◽  
Vol 176 ◽  
pp. 135-136
Author(s):  
Toshiki Aikawa

AbstractSome pulsating post-AGB stars have been observed with an Automatic Photometry Telescope (APT) and a considerable amount of precise photometric data has been accumulated for these stars. The datasets, however, are still sparse, and this is a problem for applying nonlinear time series: for instance, modeling of attractors by the artificial neural networks (NN) to the datasets. We propose the optimization of data interpolations with the genetic algorithm (GA) and the hybrid system combined with NN. We apply this system to the Mackey–Glass equation, and attempt an analysis of the photometric data of post-AGB variables.


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