LATENT O‘QUV JARAYONLARINI GEOMETRIK MODELLASHTIRISH ASOSIDA TAHLIL QILISH
DOI:
https://doi.org/10.65164/qqt33c28Kalit so‘zlar:
latent jarayonlar, geometrik modellashtirish, virtual reallik, elektrofor mashina, elektrostatika, 3D vizualizatsiya.Abstrak
Mazkur tadqiqotda latent jarayonlarni aniqlash hamda ularni geometrik modellashtirish asosida tahlil qilish masalalari yoritilgan. Ish doirasida tadqiqot obyekti sifatida elektrofor mashinada yuzaga keladigan elektrostatik hodisalar tanlab olindi. Ushbu jarayonlar davomida zaryadlarning fazoviy taqsimlanishi, elektr potensial hamda maydon kuchlanganligi kabi fizik kattaliklar to‘g‘ridan-to‘g‘ri kuzatilmaydigan, ya’ni yashirin (latent) parametrlar sifatida qaraladi.
Havolalar
1. 3D TEXNOLOGIYALARNI TALIMDAGI O‘RNI Artikova M.A, Bahromov A.A., Jo‘raboyev. F.A. https://zenodo.org/records/14807836
2. Azamatova N. Virtual reallik texnologiyalari asoslari va ularning ta’limda qo‘llanilishi. – Toshkent: Innovatsiya markazi nashriyoti, 2022.
227
3. VIRTUAL REALLIK TEXNOLOGIYALARINING MATEMATIK MODELLARINI TAHLIL QILISH Jo‘raboyev F.A., Bahromov A.A. https://doi.org/ 10.5281/zenodo.14857556
4. Artikova M.A., Sayfiyev E.E., Juraboev F.A. Virtual va toʻldirilgan reallik texnologiyalari asosida “Oʻzbekiston boʻyicha adabiy qoʻllanma” qoʻllanmasining elektron platformasi va mobil ilovasini yaratish // Universum: texnika fanlari: elektron. ilmiy jurnal. 2022. 10(103).
URL: https://7universum.com/ru/tech/archive/item/14440.
5. Pearson K. On lines and planes of closest fit to systems of points in space // Philosophical Magazine. – 1901. – Vol. 2. – P. 559–572.
6. Hotelling H. Analysis of a complex of statistical variables into principal components // Journal of Educational Psychology. – 1933. – Vol. 24. – P. 417–441.
7. Hinton G., Salakhutdinov R. Reducing the dimensionality of data with neural networks // Science. – 2006. – Vol. 313. – P. 504–507.
8. Tenenbaum J., de Silva V., Langford J. A global geometric framework for nonlinear dimensionality reduction // Science. – 2000. – Vol. 290. – P. 2319–2323.
9. Maaten L., Hinton G. Visualizing data using t-SNE // Journal of Machine Learning Research. – 2008. – Vol. 9. – P. 2579–2605.
10. McInnes L., Healy J., Melville J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction // arXiv preprint. – 2018.
11. Poisson S.D. Sur la distribution de l’électricité // Journal de l’École Polytechnique. – 1813.
12. Laplace P.S. Traité de mécanique céleste. – Paris, 1785.
13. Raissi M., Perdikaris P., Karniadakis G. Physics-informed neural networks // Journal of Computational Physics. – 2019. – Vol. 378. – P. 686–707.
14. Slater M. Immersion and the illusion of presence in virtual reality // British Journal of Psychology. – 2009.
15. Bailenson J. Experience on Demand: What Virtual Reality Is, How It Works, and What It Can Do. – New York: W.W. Norton, 2018.
16. Modeling and interactive visualization of the spatial structure of latent processes using virtual reality technologies. Artikova M.A., Joʻraboyev F.A. https://uzjurnal.uz/2/2026/1/index?issue=4
