Open AccessForecasting the cost of quotes using LSTM & GRU networks
Author(s) -
Roman Sergeevich Ekhlakov,
Vladimir Anatolievich Sudakov
Publication year - 2022
Publication title -
keldysh institute preprints
Language(s) - English
Resource type - Journals
eISSN - 2071-2901
pISSN - 2071-2898
DOI - 10.20948/prepr-2022-17
Subject(s) - recurrent neural network , computer science , long short term memory , artificial intelligence , software , artificial neural network , machine learning , programming language
The paper considers modern recurrent neural networks (RNN). Most attention is paid to popular and powerful architectures – long chain of elements of short-term memory (LSTM) and controlled recurrent units (GRU). A software package for forecasting the cost of quotations has been written and a comparison of two methods has been made.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom