KATTA MA’LUMOTLAR ASOSIDA TURISTIK XIZMATLARGA BO‘LGAN TALABNI PROGNOZLASHNING IQTISODIY-MATEMATIK MODELINI ISHLAB CHIQISH
DOI:
https://doi.org/10.5281/zenodo.21539100Ключевые слова:
katta ma’lumotlar, turistik talab, prognozlash, SARIMA, LSTM, Google Trends, OTA, gibrid model, MAPE, RevPAR.Аннотация
Ushbu maqolada katta ma’lumotlar asosida turistik xizmatlarga bo‘lgan talabni
prognozlashning gibrid iqtisodiy-matematik modeli ishlab chiqilgan. Taklif etilgan model SARIMA ekonometrik
komponenti, LSTM neyron tarmog‘i va BD(t) real vaqt rejimidagi katta ma’lumotlar signalini ansambl tizimida
birlashtiradi. Model o‘zgaruvchilari sifatida makroiqtisodiy omillar, Google Trends qidiruv indeksi, OTA bronlash
tezligi, ijtimoiy tarmoqlardagi sentiment indeksi, aviareyslar mavjudligi va boshqa omillar tanlangan. Kalibrlash
natijalariga ko‘ra, gibrid model bir oylik bashorat gorizontida MAPE ko‘rsatkichi bo‘yicha 5,1 foiz va R² ko‘rsatkichi
bo‘yicha 0,91 natijani qayd etgan. Model turizm korxonalarida resurslarni maqbul taqsimlash, dinamik narxlash
va marketing qarorlarini qo‘llab-quvvatlashga xizmat qiladi.
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