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JOURNALS // Preprints of the Keldysh Institute of Applied Mathematics // Archive

Keldysh Institute preprints, 2022 017, 13 pp. (Mi ipmp3043)

This article is cited in 1 paper

Forecasting the cost of quotes using LSTM & GRU networks

R. S. Ekhlakov, V. A. Sudakov


Abstract: 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.

Keywords: RNN, LSTM, GRU, forecasting the cost of quotes.

DOI: 10.20948/prepr-2022-17



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