Using Neuronets to Forecast Economic Processes in Conditions of Uncertainty

Lately we can observe the trend of fast development of neuronet technologies. Neuronets are researched by different sciences: economic, mathematic, informational, statistic, etc. Advantages of using neuronets in various types of activities are as follows: adaptability, possibility to process big amounts of variables, high degree of reliability and opportunity to retune the model when parameters are changed. Models of neuronet forecasting are widely used in finance and economic field, as it often uses analytical indicators. The article shows benefits of neuronet models in comparison with traditional ways of processing information to forecast economic figures. Neuronets give an opportunity to trace dynamics of various economic indicators: inflation rate, consumer prices, human capital, etc. Apart from that neuronets can be combined with other ways of information processing, for example, economic ones, which can provide extra opportunities of their use. The authors show prospects of neuronet development in analytical systems.