Raqamli texnologiyalarning Yangi O‘zbekiston rivojiga ta’siri

O‘ZBEKISTON
 RIVOJIGA 
TA’SIRI
 
Xalqaro ilmiy-amaliy konferensiyasi
 
4-
SHO‘BA.
 ILMIY VA TEXNIK ISHLANMALAR SOHASIDA INNOVATSIYALARNI 
ISHLAB CHIQISHDA RAQAMLI TEXNOLOGIYALARDAN FOYDALANISH 

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209 
 
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 of Namangan State University (Uzbekistan) 
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. 
Keywords:
Gross Domestic Product (GDP), GDP growth, machine learning algorithms, 
random forest regression, linear regression, autoregressive integrated moving average (ARIMA), 
forecasting, economic analysis, decision-making. 
Introduction
Gross Domestic Product is the total monetary value of the all the finished goods and services 
produced within a country in a specific time period. [Dwarakanath G V, (2022)]
. Calculating real 
GDP involves comparing the most recent year’s real GDP with the previous year’s real GDP and then 
dividing the difference by the prior year’s real GDP. Alternatively, real GDP can be derived by 
considering the nominal GDP and the prevailing inflation rate. Understanding GDP and its growth 
is essential for evaluating the strength and trajectory of an economy. 
Today, nations around the world are actively striving to increase their GDP and GDP per 
capita, which is the ratio of total GDP to the population. This metric offers insights into the living 
standards of a country’s citizens. Consequently, GDP becomes a vital yardstick for policymakers, 
economists, and researchers when analyzing and predicting future economic levels. Researchers 
employ various methods, models, and tools to forecast GDP accurately. While traditional methods 
and models have been widely used, they often fall short of providing satisfactory results. As a result, 
more sophisticated and precise approaches have emerged. Among these is the utilization of 
machine learning algorithms (ML), a branch of artificial intelligence (AI) and data science (DS). 
Machine learning algorithms offer a promising avenue for GDP prediction due to their ability 
to analyze vast amounts of data, identify patterns, and make accurate forecasts. By leveraging ML 
techniques, economists and researchers can incorporate a wide range of economic, financial, and 

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