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Modeling and Predicting Time Series with Non-stationarity and Volatility

The difficulty of time series prediction lies in how to handle non-stationarity and volatility. When dealing with non-stationarity, existing deep learning models adopt a method of stabilizing the input sequences before training, which has problems of weak ability to eliminate non-stationarity or los...

Täydet tiedot

Tallennettuna:
Päätekijä: FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning
Aineistotyyppi: Artigo
Kieli:Chinês
Julkaistu: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2025-05-01
Sarja:Jisuanji kexue yu tansuo
Aiheet:
time series prediction; non-stationarity; high volatility; long short-term memory neural network; multi-head self-attention
Linkit:http://fcst.ceaj.org/fileup/1673-9418/PDF/2407096.pdf
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