Neuroevolution Forecasting of the Living Standards of the Population

Abstract

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.

Baikal Region (Russia) Development Prospects Based on the Green Economy Principles

“…In this study, using the Baikal region example, this method was tested and showed good results. Therefore, to forecast the eco-socio-economic development of the Baikal region, we chose artificial neural networks with automatic topology construction, particularly the forecasting method proposed in [27,28], and the software developed on its basis [30]. This forecasting technique is based on the use of a multilayer perceptron (MLP) [39] in combination with evolutionary calculations [40,41].…”

“…In the forecasting methodology and the program [27,28,30], the neural network training algorithm was used using the NEAT method, which uses a genetic algorithm and automatically builds the neural network topology in the learning process [44]. This method trains neural networks for target indicators.…”

“…The region's eco-socio-economic system characterizes by the fact that it has a certain potential and uses the available opportunities for dynamic development. We choose neural network models as a forecasting method [27,28] because it is good at solving problems where statistical methods work poorly. It predicted future trends in the development of the region's system and gave recommendations for policy changes and proposed regulatory mechanisms to promote the introduction and use of the green economy principles.…”