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APSO-TA-LSTM: a long and short term memory model combining time attention and adaptive particle swarm optimization for stock forecasting.

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Title: APSO-TA-LSTM: a long and short term memory model combining time attention and adaptive particle swarm optimization for stock forecasting.
Authors: Hao, Tianyu1, Song, Gang2, gangs@mail.sdu.edu.cn, Du, Hongwei2
Source: International Journal of General Systems; Oct2023, Vol. 52 Issue 7, p876-893, 18p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 171310484
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PubType: Academic Journal
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  Data: APSO-TA-LSTM: a long and short term memory model combining time attention and adaptive particle swarm optimization for stock forecasting.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+General+Systems%22">International Journal of General Systems</searchLink>; Oct2023, Vol. 52 Issue 7, p876-893, 18p
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/03081079.2023.2222888
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 876
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      – TitleFull: APSO-TA-LSTM: a long and short term memory model combining time attention and adaptive particle swarm optimization for stock forecasting.
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            NameFull: Hao, Tianyu
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            NameFull: Song, Gang
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            NameFull: Du, Hongwei
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            – D: 01
              M: 10
              Text: Oct2023
              Type: published
              Y: 2023
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              Value: 52
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              Value: 7
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            – TitleFull: International Journal of General Systems
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