Open AccessForecasting the cost of quotes using LSTM & GRU networks
Author(s) -
Roman Sergeevich Ekhlakov,
Vladimir Anatolievich Sudakov
Publication year - 2022
Publication title -
preprint/preprinty ipm im. m.v. keldyša
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.