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A Method for Reconstructing State Information of Ship Integrated Power System Distribution Networks Under Incomplete Data Conditions.

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Title: A Method for Reconstructing State Information of Ship Integrated Power System Distribution Networks Under Incomplete Data Conditions.
Authors: Peng, Yonglin1 (AUTHOR), Huang, Jing1 (AUTHOR), Pan, Bingchen1 (AUTHOR), Liu, Haijun1 (AUTHOR), Xiao, Han1 (AUTHOR) 1810061109@nue.edu.cn
Source: Energies (19961073). May2026, Vol. 19 Issue 10, p2266. 18p.
Subject Terms: *Metaheuristic algorithms, *Back propagation, *Electric power systems, *Optimization algorithms, *Electric power distribution grids, *Real-time computing
Abstract: To address non-complete data issues such as missing, distorted, redundant and chaotic data in distribution network condition monitoring data easily caused by ship faults (e.g., sensor failure, cable short circuit, etc.), an improved optimization algorithm (IPS-SH5N1) considering the demand for incomplete information reconstruction in the distribution network of ship integrated power systems is proposed based on the SH5N1 meta-heuristic optimization algorithm. This algorithm is used to optimize the weights and thresholds of a BPNN, achieving accurate completion of non-complete information in the distribution network. The IPS-SH5N1-BPNN is applied to conduct information reconstruction verification on 2000 groups of incomplete data samples of ship integrated power systems. The results show that the information reconstruction accuracy (MSE) of this method is improved by more than 90% compared with the BPNN; the model training convergence time and global optimization time consumption are significantly shortened, and the average online single information reconstruction time is reduced to 4.45 ms. This method has core advantages of high precision, fast convergence, strong robustness and excellent real-time performance, which can provide reliable technical support for the intelligent operation and maintenance of ship integrated power systems. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194141381
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: A Method for Reconstructing State Information of Ship Integrated Power System Distribution Networks Under Incomplete Data Conditions.
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  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Peng%2C+Yonglin%22">Peng, Yonglin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Jing%22">Huang, Jing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Bingchen%22">Pan, Bingchen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Haijun%22">Liu, Haijun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiao%2C+Han%22">Xiao, Han</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 1810061109@nue.edu.cn</i>
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  Label: Source
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 10, p2266. 18p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Back+propagation%22">Back propagation</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+power+systems%22">Electric power systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+power+distribution+grids%22">Electric power distribution grids</searchLink><br />*<searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To address non-complete data issues such as missing, distorted, redundant and chaotic data in distribution network condition monitoring data easily caused by ship faults (e.g., sensor failure, cable short circuit, etc.), an improved optimization algorithm (IPS-SH5N1) considering the demand for incomplete information reconstruction in the distribution network of ship integrated power systems is proposed based on the SH5N1 meta-heuristic optimization algorithm. This algorithm is used to optimize the weights and thresholds of a BPNN, achieving accurate completion of non-complete information in the distribution network. The IPS-SH5N1-BPNN is applied to conduct information reconstruction verification on 2000 groups of incomplete data samples of ship integrated power systems. The results show that the information reconstruction accuracy (MSE) of this method is improved by more than 90% compared with the BPNN; the model training convergence time and global optimization time consumption are significantly shortened, and the average online single information reconstruction time is reduced to 4.45 ms. This method has core advantages of high precision, fast convergence, strong robustness and excellent real-time performance, which can provide reliable technical support for the intelligent operation and maintenance of ship integrated power systems. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.3390/en19102266
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 2266
    Subjects:
      – SubjectFull: Metaheuristic algorithms
        Type: general
      – SubjectFull: Back propagation
        Type: general
      – SubjectFull: Electric power systems
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Electric power distribution grids
        Type: general
      – SubjectFull: Real-time computing
        Type: general
    Titles:
      – TitleFull: A Method for Reconstructing State Information of Ship Integrated Power System Distribution Networks Under Incomplete Data Conditions.
        Type: main
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            NameFull: Peng, Yonglin
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            NameFull: Huang, Jing
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            NameFull: Pan, Bingchen
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            NameFull: Liu, Haijun
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            NameFull: Xiao, Han
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          Dates:
            – D: 15
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 19961073
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              Value: 19
            – Type: issue
              Value: 10
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            – TitleFull: Energies (19961073)
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