Work

Time Series Determinism Recognition by LSTM Model

Year: 2025
Type: article
Abstract: The problem of time series determinism measurement is investigated. It is shown that a deep learning model can be used as a determinism measure of a time series. Three distinct time series classes were utilised to verify the feasibility of differentiating deterministic time series: deterministic, deterministic with noise, and stochastic. The LSTM model was constructed for each time series, and its features were thoroughly investigated. The findings of this study demonstrate a strong correlation between the root mean square error (RMSE) of the trained models and the determinism of a time series.
Source: Mathematics
Language: English
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4411369156
FWCI: 0.42
Cites: 40
Cited by: 1
Related to: 10