ECONOMIC FORECASTING USING ARTIFICIAL INTELLIGENCE MODELS AND ALGORITHMS IN THE CASE OF UZBEKISTAN

Ulug'bek Bekmurodov; Diyora Absalamova; Guzal Absalamova

Авторы

Ulug'bek Bekmurodov Tashkent State University of Economics
Diyora Absalamova Tashkent State University of Economics
Guzal Absalamova Samarkand State University

Ключевые слова:

AI models, LSTM networks, Random Forests, economic forecasting

Аннотация

The economic landscape of Uzbekistan is dynamic and influenced by various factors. Forecasting economic variables is key to developing a view on a country's economic outlook. Accurate prediction of economic indicators is crucial for effective policy making, resource allocation, and strategic planning. In recent years, the integration of artificial intelligence (AI) models and algorithms has shown promise in enhancing the precision of economic forecasts. We apply the LSTM networks and Random Forests algorithms on several economic data. This study aims to leverage AI techniques for predicting key economic indicators in the context of Uzbekistan. The chosen AI models and algorithms will be applied to relevant economic datasets, and the results will be analyzed to assess their efficacy in forecasting.

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