NEYRON TARMOQLAR ASOSIDA IQTISODIY KO‘RSATKICHLARNI BASHORAT QILISHNING AHAMIYATI VA AFZALLIKLARI
Keywords:
Kalit so‘zlar: iqtisodiy bashoratlash, neyron tarmoqlar, sun’iy intellekt, LSTM, GRU, CNN, ARIMA, VAR, Big Data, iqtisodiy modellashtirish, vaqt qatorlari, Deep LearningAbstract
Annotatsiya: Mazkur maqolada iqtisodiy ko‘rsatkichlarni bashorat qilishning nazariy asoslari, zamonaviy usullari hamda sun’iy neyron tarmoqlarning ushbu jarayondagi o‘rni va ahamiyati tahlil qilingan. Iqtisodiy prognozlashda qo‘llaniladigan an’anaviy statistik modellar, jumladan ARIMA va VAR modellari hamda sun’iy intellekt asosidagi yondashuvlar o‘zaro taqqoslangan. Neyron tarmoqlarning no-chiziqli bog‘liqliklarni aniqlash, katta hajmdagi ma’lumotlar bilan ishlash, uzoq muddatli prognozlash va iqtisodiy jarayonlarga moslashish kabi afzalliklari yoritilgan. Shuningdek, LSTM, GRU, CNN va Transformer modellarining iqtisodiy vaqt qatorlarini tahlil qilishdagi imkoniyatlari ko‘rib chiqilgan. Tadqiqot natijalari shuni ko‘rsatadiki, neyron tarmoqlar iqtisodiy ko‘rsatkichlarni bashoratlashda an’anaviy modellar bilan solishtirganda yuqoriroq aniqlik va moslashuvchanlikni ta’minlaydi hamda zamonaviy iqtisodiy boshqaruv tizimlarining muhim tarkibiy qismi hisoblanadi.
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