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Preprints of the Keldysh Institute of Applied Mathematics, 2022, 017, 13 pp.
DOI: https://doi.org/10.20948/prepr-2022-17 (Mi ipmp3043) 		 
This article is cited in 1 scientific paper (total in 1 paper)

Forecasting the cost of quotes using LSTM & GRU networks

R. S. Ekhlakov, V. A. Sudakov
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DOI: https://doi.org/10.20948/prepr-2022-17
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.
Document Type: Preprint
Language: Russian
Citation: R. S. Ekhlakov, V. A. Sudakov, “Forecasting the cost of quotes using LSTM & GRU networks”, Keldysh Institute preprints, 2022, 017, 13 pp.
Citation in format AMSBIB
\Bibitem{EkhSud22}
\by R.~S.~Ekhlakov, V.~A.~Sudakov
\paper Forecasting the cost of quotes using LSTM \&\ GRU networks
\jour Keldysh Institute preprints
\yr 2022
\papernumber 017
\totalpages 13
\mathnet{http://mi.mathnet.ru/ipmp3043}
\crossref{https://doi.org/10.20948/prepr-2022-17}
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  • https://www.mathnet.ru/eng/ipmp/y2022/p17
    • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Препринты Института прикладной математики им. М. В. Келдыша РАН
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