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The article is devoted to the problem of forecasting indicators of living standards using neuroevolutionary approach. The NEAT method is considered that allows generating the neural network topology automatically. The paper proposes modification of this method and its implementation based on the activation functions mutation, which enabled to expand the set of possible solutions. A comparative analysis of the training, testing, and forecasting accuracy is carried out. Target indicator forecasting was performed with preliminary forecasting of factor signs that increased forecasting accuracy in comparison to the Windows method used to forecast target indicators directly.

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