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Prediction and calibration of black soil modeling parameters based on response surface methodology and machine learning algorithms.

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Title: Prediction and calibration of black soil modeling parameters based on response surface methodology and machine learning algorithms.
Authors: Wang, Zhipeng1, 448465250@qq.com, Ma, Feng2, Zhu, Yaonan3, Wang, Hongyan4, Zhu, Tong1, tongzhu@mail.neu.edu.cn, Wang, Youzhao1, wangyz@me.neu.edu.cn, Zhao, Chaoyue1, Yu, Jin5
Source: Particulate Science & Technology; 2025, Vol. 43 Issue 4, p534-545, 12p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 184628260
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Prediction and calibration of black soil modeling parameters based on response surface methodology and machine learning algorithms.
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  Data: <searchLink fieldCode="JN" term="%22Particulate+Science+%26+Technology%22">Particulate Science & Technology</searchLink>; 2025, Vol. 43 Issue 4, p534-545, 12p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=184628260
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/02726351.2025.2476672
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 534
    Titles:
      – TitleFull: Prediction and calibration of black soil modeling parameters based on response surface methodology and machine learning algorithms.
        Type: main
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          Name:
            NameFull: Wang, Zhipeng
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            NameFull: Ma, Feng
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            NameFull: Zhu, Yaonan
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            NameFull: Wang, Hongyan
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            NameFull: Zhu, Tong
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            NameFull: Wang, Youzhao
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            NameFull: Zhao, Chaoyue
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            NameFull: Yu, Jin
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          Dates:
            – D: 01
              M: 05
              Text: 2025
              Type: published
              Y: 2025
          Identifiers:
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              Value: 02726351
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              Value: 43
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Particulate Science & Technology
              Type: main
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