ILMIY TADQIQOTLARDA SUN’IY INTELLEKT TEXNOLOGIYALARIDAN FOYDALANISHNING ZAMONAVIY YO‘NALISHLARI VA ISTIQBOLLARI

Authors

  • Hamidullayev F.L University of Tashkent for Applied Sciences image/svg+xml Author
  • Xalilova U.A. O`zbekiston Milliy Universiteti magistrlari Author

DOI:

https://doi.org/10.65164/01mmv760

Keywords:

sun’iy intellekt, ilmiy tadqiqotlar, mashinali o‘rganish, raqamli texnologiyalar, innovatsiya, katta ma’lumotlar (Big Data).

Abstract

Ushbu maqolada ilmiy tadqiqotlar jarayonida sun’iy intellekt texnologiyalaridan foydalanishning zamonaviy yo‘nalishlari, ularning ilm-fan taraqqiyotidagi o‘rni va kelajakdagi istiqbollari tahlil qilinadi. Tadqiqotda mashinali o‘rganish, chuqur o‘rganish hamda katta ma’lumotlar texnologiyalarining ilmiy izlanishlar samaradorligini oshirishdagi ahamiyati yoritib berilgan. Scopus va Web of Science bazalarida indekslangan ilmiy manbalar asosida sun’iy intellektning biologiya, tibbiyot, ekologiya va boshqa fan sohalaridagi qo‘llanilish holati o‘rganilgan. Tadqiqot natijalari sun’iy intellekt ilmiy jarayonlarni avtomatlashtirish, ma’lumotlarni tezkor va aniq tahlil qilish hamda ilmiy natijalarning ishonchliligini oshirishda muhim vosita ekanini ko‘rsatadi. Shuningdek, sun’iy intellektdan foydalanish bilan bog‘liq muammolar va etik masalalar ham muhokama qilinadi.

References

1. Russell, S., Norvig, P. Artificial Intelligence: A Modern Approach. Pearson Education, 2021.

2. Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. MIT Press, 2016.

3. Jordan, M. I., Mitchell, T. M. Machine learning: Trends, perspectives, and prospects. Science, 2015, 349(6245), 255–260.

4. LeCun, Y., Bengio, Y., Hinton, G. Deep learning. Nature, 2015, 521, 436–444.

5. Bishop, C. M. Pattern Recognition and Machine Learning. Springer, 2006.

6. Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 2019, 25, 44–56.

7. Esteva, A. et al. A guide to deep learning in healthcare. Nature Medicine, 2019, 25, 24–29.

8. Chen, X., Xie, H., Zou, Y. Artificial intelligence in scientific research. Journal of Informetrics, 2020, 14(4), 101–112.

9. Kitchin, R. Big data, new epistemologies and paradigm shifts. Big Data & Society, 2014, 1(1).

10. Floridi, L. et al. AI4People—An ethical framework for a good AI society. Minds and Machines, 2018, 28, 689–707.

11. Wang, L., Alexander, C. Big data analytics in scientific discovery. IEEE Access, 2020, 8, 123–135.

12. Nielsen, M. A. Reinventing discovery: The new era of networked science. Princeton University Press, 2011.

13. Hey, T., Tansley, S., Tolle, K. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research, 2009.

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Published

2025-12-29