
Mazkur tadqiqotda samolyot qanotining aerodinamik ko‘rsatkichlarini tezkor va yuqori aniqlik bilan bashorat qilish hamda optimal geometrik shaklini aniqlashga yo‘naltirilgan integratsiyalashgan sun’iy intellektga asoslangan hisoblash tizimi taklif etiladi. O‘qitish ma’lumotlari fizik qonunlarga asoslangan sintetik belgilash generatori yordamida shakllantirildi. An’anaviy hisoblash suyuqliklar mexanikasi usullariga (CFD) xos bo‘lgan katta hisoblash xarajatlari va vaqt sarfini kamaytirish maqsadida ko‘tarish koeffitsienti (CL) hamda qarshilik koeffitsienti (CD) ni baholash uchun sun’iy neyron tarmoqqa asoslangan muqobil model ishlab chiqildi.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
