Modeling and Forecasting Production Indices Using Artificial Neural Networks, Taking Into Account Intersectoral Relationships and Comparing the Predictive Qualities of Various Architectures

Abstract

This paper analyzes the possibilities of using convolutional and recurrent neural networks to predict the indices of industrial production of the Russian economy. Since the indices are asymmetric in periods of growth and decline, it was hypothesized that nonlinear methods will improve the quality of the forecast relative to linear ones.

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