LSTM TARMOQLARINING MOHIYATI VA MOLIYAVIY PROGNOZLASHDAGI AHAMIYATI
Ключевые слова:
Kalit soʻzlar: LSTM, moliyaviy prognozlash, vaqt seriyalari, uzoq muddatli xotira, sunʼiy neyron tarmoq, deep learning, ketma-ketlik, overfitting, real vaqtli prognozlash, hybrid modelАннотация
Annotatsiya
Ushbu maqolada LSTM (Long Short-Term Memory) tarmoqlarining mohiyati
va ularning moliyaviy prognozlashdagi qoʻllanilishi haqida tushuncha berilgan. LSTM
tarmoqlarining vaqt boʻyicha ketma-ketlikdagi maʼlumotlarni samarali qayta ishlash
xususiyati moliyaviy prognozlashda yuqori natijadorlikka ega ekanligi tahlil qilinadi.
Shuningdek, bu tarmoqlarning imkoniyatlari va cheklovlari ham koʻrib chiqiladi.
Библиографические ссылки
Foydalanilgan Adabiyotlar
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