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FARMATSEVTIKA BOZORIDA TALAB VA TAKLIFNIPROGNOZLASHDA SUNʼIY INTELLEKT ALGORITMLARIDANFOYDALANISH

Опубликован 2026-04-03

Авторы
Xomidov Soxibmalik Olimovich
pdf (узбекский) Google Scholar Google Scholar

Аннотация

Ushbu ilmiy maqolada farmatsevtika bozorida talab va taklifni prognozlashda
sunʼiy intellekt (SI) algoritmlaridan foydalanish masalalari tadqiq etilgan. Maqsad:
farmatsevtika sohasida SI asosidagi prognozlash modellarini qiyosiy tahlil qilish va
Oʻzbekiston farmatsevtika bozori uchun eng samarali algoritmni aniqlash.
Metodologiya: mashinali oʻqitish (ML) algoritmlari – LSTM, Random Forest,
XGBoost, Prophet – 2018–2024 yillar uchun Oʻzbekiston farmatsevtika bozori
maʼlumotlari asosida sinab koʻrildi. RMSE, MAE va MAPE koʻrsatkichlari asosida
algoritmlar qiyosiy baholandi. Natijalar: LSTM neyron tarmogʻi eng yuqori aniqlikni
koʻrsatdi (MAPE=4.2%), XGBoost esa tezligi va talqin qilish qulayligi bilan ajralib
turdi. Xulosa: Gibrid SI-modellari (LSTM+XGBoost) Oʻzbekiston farmatsevtika
bozorida talab-taklifni real vaqtda prognozlash uchun optimal yechim hisoblanadi.

Ключевые слова

sunʼiy intellekt, farmatsevtika bozori, talab prognozi, taklif prognozi, mashinali oʻqitish, LSTM, XGBoost, Random Forest, Prophet, Oʻzbekiston.

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