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Hourly Sea Level Prediction‐Based GNSS‐IR Inversions by Combining the Least Squares Learning Cross‐Checking Method With the Gaussian Kernel Model L2 Constraint and LSTM.

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Title: Hourly Sea Level Prediction‐Based GNSS‐IR Inversions by Combining the Least Squares Learning Cross‐Checking Method With the Gaussian Kernel Model L2 Constraint and LSTM.
Authors: Zheng, Naiquan1,2 (AUTHOR) Naiquan_Z@outlook.com, Chai, Hongzhou1 (AUTHOR), Ma, Yongchao3 (AUTHOR), Chen, Lingqiu1,2 (AUTHOR), Wang, Min1 (AUTHOR), Bai, Tengfei1 (AUTHOR)
Source: Earth & Space Science. Mar2023, Vol. 10 Issue 3, p1-19. 19p.
Database: Academic Search Ultimate
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  Data: Hourly Sea Level Prediction‐Based GNSS‐IR Inversions by Combining the Least Squares Learning Cross‐Checking Method With the Gaussian Kernel Model L2 Constraint and LSTM.
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  Data: <searchLink fieldCode="JN" term="%22Earth+%26+Space+Science%22">Earth & Space Science</searchLink>. Mar2023, Vol. 10 Issue 3, p1-19. 19p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=162757183
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1029/2022EA002660
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      – Code: eng
        Text: English
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        PageCount: 19
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      – TitleFull: Hourly Sea Level Prediction‐Based GNSS‐IR Inversions by Combining the Least Squares Learning Cross‐Checking Method With the Gaussian Kernel Model L2 Constraint and LSTM.
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            NameFull: Chai, Hongzhou
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            NameFull: Ma, Yongchao
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            NameFull: Chen, Lingqiu
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            NameFull: Wang, Min
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            – D: 01
              M: 03
              Text: Mar2023
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              Y: 2023
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