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- W2023177064 abstract "The aim of the study was to investigate the possibility of generating and using neural models for predicting the lowest and highest daily rates of consumption wheat in the Forex market. Input parameters and prepared learning sets of neural network are analysed with a view to generating neural models. After the artificial neural networks were generated, a sensitivity analysis was done and the learning set rebuilt. The set data required to properly forecast prices were added to the new training." @default.
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- W2023177064 date "2014-01-01" @default.
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- W2023177064 title "Modele neuronowe wspomagające prognozowanie cen pszenicy konsumpcyjnej na zdecentralizowanym rynku towarowym" @default.
- W2023177064 doi "https://doi.org/10.15678/znuek.2014.0935.1107" @default.
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