A hybrid deep learning approach for enhancing the Lorentzian curve fit algorithm for Schumann resonance.

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Title: A hybrid deep learning approach for enhancing the Lorentzian curve fit algorithm for Schumann resonance.
Authors: Cano-Domingo, Carlos1,2, Stoean, Ruxandra1,3,4,5, ruxandra.stoean@inf.ucv.ro, Joya, Gonzalo6, Novas, Nuria7, Fernández-Ros, Manuel7, Gázquez Parra, Jose A.7
Source: Expert Systems with Applications; Dec2025, Vol. 293, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 187943247
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A hybrid deep learning approach for enhancing the Lorentzian curve fit algorithm for Schumann resonance.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187943247
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.eswa.2025.128681
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: A hybrid deep learning approach for enhancing the Lorentzian curve fit algorithm for Schumann resonance.
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            NameFull: Cano-Domingo, Carlos
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            NameFull: Stoean, Ruxandra
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            NameFull: Joya, Gonzalo
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            NameFull: Novas, Nuria
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            NameFull: Fernández-Ros, Manuel
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            NameFull: Gázquez Parra, Jose A.
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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              Value: 293
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            – TitleFull: Expert Systems with Applications
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