ECONOMIC FORECASTING USING ARTIFICIAL INTELLIGENCE MODELS AND ALGORITHMS IN THE CASE OF UZBEKISTAN
Keywords:
AI models, LSTM networks, Random Forests, economic forecastingAbstract
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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Copyright (c) 2023 Ulugbek Bekmurodov, Diyora Absalamova, Guzal Absalamova
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