The article discusses the theoretical and practical foundations of forecasting investments in the regions of Uzbekistan using neural networks, the basic principles of the functioning of neural network technologies, analyzes the main software products used in the forecasting tasks, identifies the main directions of investment policy, providing a set of measures to strengthen the positive growth trends investment in the regions of Uzbekistan, the proposed method of forecasting attractiveness and investments in regions with the use of neural network-type multi-layer perceptron, given suggestions to improve the investment climate in the country.
The article discusses neural networks that are widely used in various fields, such as economics (prediction of stock market indicators, prediction of financial time series), robotics (recognition of optical and audio signals, self-learning), visualization of multidimensional data, associative search for textual information, etc.
Neural networks are of interest to a fairly large number of specialists, for example for computer scientists’ neural networks open up the field of new methods for solving complex problems; physicists use neural networks to model phenomena in statistical mechanics and to solve many other problems: neurophysiologists can use neural networks to model and study brain functions; psychologists have at their disposal a mechanism for testing models of some of their psychological theory.
Saidakhror Gulyamov, Abbas Shermukhamedov, Bokhodir Kholboev