FORECASTING THE ECONOMIC COMPETITIVENESS OF THE SAMARKAND REGION BASED ON BIG DATA TECHNOLOGY

Shuhrat Kamalovich Kamalov
Tashkent State University of Economics
Associate Professor, Department of Artificial Intelligence
Email: [email protected]
Tashkent, Uzbekistan
ORCID: 0000-0003-4937-0814

Diyora Bo‘riboyevna Absalamova
Tashkent State University of Economics
Assistant, Department of Artificial Intelligence
Email: [email protected]
Tashkent, Uzbekistan

Go‘zal Bo‘riboyevna Absalamova
Tashkent State University of Economics
Senior Lecturer, Department of Artificial Intelligence
Email: [email protected]
Tashkent, Uzbekistan

JELClassification: R11 O24

Abstract: This article is dedicated to analyzing the economic competitiveness of the Samarkand region using Big Data technologies and developing development forecasts for the years 2025-2030. The study processes large volumes of data, including the region’s Gross Regional Product (GRP), tourism sector, agriculture, industrial production, and infrastructure. Machine learning algorithms such as Decision Trees and Long Short-Term Memory (LSTM) are applied. The results identify the region’s economic growth potential, competitive advantages, and weaknesses, providing recommendations for improving regional development policies.
Keywords: Big Data, economic competitiveness, forecasting, Samarkand region, tourism, decision tree, LSTM, ARIMA, Apache Spark

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