Ключевые слова
Аннотация
Mazkur maqolada astronomik kuzatuv jarayonlarini raqamli transformatsiya qilish va ularni sun'iy intelekt asosida optimallashtirish muammosi ko'rib chiqiladi [1]. An'anaviy observatoriya tizimlarida kuzatuv aniqligi, real vaqt ma'lumotlarni qayta ishlash tezligi hamda tashqi muhit omillariga moslashuvchanlik yetarli darajada emasligi ilmiy asoslanadi [2]. Shu munosabat bilan avtonom boshqaruvga ega smart Observatory kontseptsiyaning fizik modeli va algoritmik arxitekturasi taklif etiladi [4].
Taklif etilayotgan yondashuv Mirzo Ulug'bek tomonidan asos solingan kuzatuv metodologiyasining zamonaviy raqamli interpretatsiyasi sifatida qaraladi [11,12]. Natijalar avtonom observatoriya tizimlarini yaratishda nazariy va amaliy asos bo'lib xizmat qilishi mumkin hamda astrofizik kuzatuvlarning yangi avlod platformasini shakllantirish istiqbollarini ochib beradi [6].
Библиографические ссылки
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Roddier, F. Adaptive Optics in Astronomy. Cambridge University Press, Cambridge, 1999.
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Bishop, C. M. Pattern Recognition and Machine Learning. Springer, New York, 2006.
Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. MIT Press, Cambridge, MA, 2016.
Dieleman, S., Willett, K. W., Dambre, J. “Rotation-invariant convolutional neural networks for galaxy morphology prediction.” Monthly Notices of the Royal Astronomical Society, vol. 450, no. 2, pp. 1441–1459, 2015.
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Tatarskii, V. I. Wave Propagation in a Turbulent Medium. McGraw-Hill, New York, 1961.
Goodman, J. W. Statistical Optics. 2nd ed., Wiley, Hoboken, NJ, 2000.
King, D. A. The Astronomy of Ulugh Beg. Variorum, Aldershot, 1994.
Pingree, D. Astronomy and Astrology in the Islamic World. Variorum, Aldershot, 1997.