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An explainable neural network integrating Jiles-Atherton and nonlinear auto-regressive exogenous models for modeling universal hysteresis

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dc.contributor.authorNi, Lei
dc.contributor.authorChen, Jie
dc.contributor.authorChen, Guoqiang
dc.contributor.authorZhao, Dongmei
dc.contributor.authorWang, Geng
dc.contributor.authorAphale, Sumeet S.
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.date.accessioned2024-07-02T14:23:00Z
dc.date.available2024-07-02T14:23:00Z
dc.date.issued2024-10-01
dc.descriptionAcknowledgements This work is supported by the Key Technologies R&D Program of Sichuan Province, China under Grant No. 23ZDYF0471, the Doctoral Research Fund of Southwest University of Science and Technology under Grant No. 22zx7140. The authors also thank the anonymous reviewers for their insightful and constructive commentsen
dc.description.statusPeer revieweden
dc.format.extent17
dc.format.extent2719896
dc.identifier290744520
dc.identifier0becafe2-ea87-4954-8aee-5c5f3ef2bf2e
dc.identifier85197074464
dc.identifier.citationNi, L, Chen, J, Chen, G, Zhao, D, Wang, G & Aphale, S S 2024, 'An explainable neural network integrating Jiles-Atherton and nonlinear auto-regressive exogenous models for modeling universal hysteresis', Engineering Applications of Artificial Intelligence, vol. 136, no. Part A, 108904. https://doi.org/10.1016/j.engappai.2024.108904en
dc.identifier.doi10.1016/j.engappai.2024.108904
dc.identifier.issn0952-1976
dc.identifier.otherORCID: /0000-0002-1691-1648/work/163196839
dc.identifier.urihttps://hdl.handle.net/2164/23745
dc.identifier.vol136en
dc.language.isoeng
dc.relation.ispartofEngineering Applications of Artificial Intelligenceen
dc.subjectPiezoelectric actuatoren
dc.subjectRate-dependent hysteresisen
dc.subjectNeural networken
dc.subjectJiles-atherton modelen
dc.subjectAsymmetricen
dc.subjectExplainabilityen
dc.subjectTA Engineering (General). Civil engineering (General)en
dc.subject.lccTAen
dc.titleAn explainable neural network integrating Jiles-Atherton and nonlinear auto-regressive exogenous models for modeling universal hysteresisen
dc.typeJournal articleen

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