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Hybrid stock price forecasting model using LSTM of attention mechanism combining noise removal and neighborhood rough set

Crossref DOI link: https://doi.org/10.1007/s10489-025-07048-2

Published Online: 2026-01-21

Published Print: 2026-01

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Guo, Yuqi

Sun, Bingzhen https://orcid.org/0000-0002-5105-8291
Bai, Juncheng

Ding, Weiping
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (72071152)

Shaanxi National Funds for Distinguished Young Scientists (2023-JC-JQ-11)

Guangzhou Municipal Science and Technology Program key projects (202206010101)

Fundamental Research Funds for the Central Universities China (20101236618, 20101236262)

Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Project (YN2022QN33)

Guangdong Basic and Applied Basic Research Foundation (2022A1515110703)
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Text and Data Mining valid from 2026-01-01

Version of Record valid from 2026-01-01
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Article History

Received: 7 February 2024

Accepted: 3 December 2025

First Online: 21 January 2026

Declarations

:

: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

: The data used in this study was sourced from the Wind database. As a user of the Wind database, this study obtained the necessary permissions and subscriptions to access and utilize the data. The usage of the data complied with the terms and conditions set by Wind Information Co., Ltd., the provider of the Wind database. These terms and conditions ensure the proper and ethical use of the data, protecting the rights and interests of the data contributors and the integrity of the database.

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