preprint
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Forecasting the cost of quotes using LSTM & GRU networks
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At a glance
- Citations
- 2
- References
- 8
- Comments
- 0
Paper overview
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.
Record transparency
Publication details
- DOI
- 10.20948/prepr-2022-17
- OpenAlex
- W4225980144
- Document type
- preprint
- Language
- EN
- Source
- Keldysh Institute Preprints
- Last metadata update
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