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Forecasting with incomplete set of factors determining the predicted factor. Neural network error extrapolation method

Andrey Gusev, Alexander Okunev

Abstract



Forecasting method that works with incomplete set of factors determining predicted factor is described in this article. The method is based on use of neural network error as a scalar value of impact of unknown factors vector on predicted factor. Authors make a conclusion that in order to forecast with required accuracy it’s necessary to extrapolate scalar value (network error).

Keywords


neural network, factor forecasting, information space compression and expansion, forecasting informational substance

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