KO‘P OMILLI STATISTIK MODELLAR YORDAMIDA O‘ZBEKISTON TASHQI SAVDO KO‘RSATKICHLARINI TAHLIL QILISH

Авторы

  • Bibisora Abdujalilova Oʻzbekiston Respublikasi Milliy Statistika qo’mitasi kadrlar malakasini oshirish va statistik tadqiqotlar instituti

Аннотация

Ushbu tadqiqotda Sun’iy intellekt texnologiyalaridan foydalanish orqali tashqi savdo jarayonlarini chuqurroq o‘rganish, resurslardan samarali foydalanish va savdo siyosatini takomillashtirish bo‘yicha nazariy va amaliy tavsiyalar ishlab chiqishga qaratilgan. Mazkur tadqiqot O‘zbekiston tashqi savdo ko‘rsatkichlarini sun’iy intellektning nazoratsiz o‘rganish yondashuvlari asosida tahlil etish, ularning determinantlarini aniqlash hamda ilmiy asoslangan iqtisodiy siyosat tavsiyalarini ishlab chiqish uchun muhim metodologik asos yaratadi.

Библиографические ссылки

Du-Harpur, X., Watt, F., Luscombe, N., & Lynch, M. (2020). What is AI? Applications of artificial intelligence to dermatology. British Journal of Dermatology, 183(3), 423–430.

Firt, E. (2023). Artificial understanding: A step toward robust AI. AI & Society, 39(4), 1653–1665.

Gewers, F. L., Ferreira, G. R., Arruda, H. F. D., Silva, F. N., Comin, C. H., Amancio, D. R., & Costa, L. D. F. (2021). Principal component analysis: A natural approach to data exploration. ACM Computing Surveys (CSUR), 54(4), 1–34.

Jakubik, A., Rotunno, L., & Saini, A. (2025, June 26). Foresee the unseen: Evaluating the impact of artificial intelligence on international trade. International Monetary Fund; University of Illinois Chicago.

Jolliffe, I. T. (2002). Principal component analysis for special types of data (pp. 338–372). Springer.

Korir, E. K. (2024). Comparative clustering and visualization of socioeconomic and health indicators: A case of Kenya. Socio-Economic Planning Sciences, 95, 101961.

Ozturk, O. (2024). The impact of AI on international trade: Opportunities and challenges. Economies, 12(11), 298. https://doi.org/10.3390/economies12110298

Salem, N., & Hussein, S. (2019). Data dimensional reduction and principal components analysis. Procedia Computer Science, 163, 292–299.

Wei, P. (n.d.). A study of principal component analysis on classifiers using histogram of gradients features [Final report]. Carnegie Mellon University. Retrieved from http://www.contrib.andrew.cmu.edu/~pwei/papers/FinalReport.pdf

World Trade Organization (WTO). (2024). World trade report 2024. Geneva: WTO Publications.

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Опубликован

2025-11-15