9
RAQAMLI TEXNOLOGIYALARNING
YANGI
O‘ZBEKISTON
RIVOJIGA
TA’SIRI
Xalqaro ilmiy-amaliy konferensiyasi
FORECASTING GROSS DOMESTIC PRODUCT (GDP) AND GDP GROWTH: AN EXPLORATION OF
IMPROVED PREDICTION USING MACHINE LEARNING ALGORITHMS
Azibaev Akhmadkhon Gulomjon ugli
PhD student, Namangan State University (Uzbekistan)
ahmadxonazibayev@gmail.com
Abstract.
This article explores the significance of Gross Domestic Product (GDP) and GDP
growth, the importance
of accurate forecasting, and the role of machine learning algorithms in
improving prediction accuracy. It reviews several studies that highlight the effectiveness of machine
learning
algorithms, such as random forest regression,
linear regression, and autoregressive
integrated moving average (ARIMA), in GDP forecasting. These algorithms analyze data, identify
patterns,
and make accurate forecasts, contributing to enhanced decision-making in economic
analysis and planning.
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