The development and application of integrated neural network models for mass appraisal and forecasting the value of residential properties on the example of the real estate markets of Yekaterinburg and Perm city

The article considers complex economic and mathematical neural network models of the residential real estate market developed by the authors, taking into account both the technical characteristics of the objects and the economic parameters of the external environment. On the example of real estate markets in Yekaterinburg and Perm, an analysis of models is carried out, which allows you to see how the change in key pricing factors affects the market value of assets. As a result of the conducted research, the degree of consumer saturation of regional markets was revealed.