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An Improved Training Method For Wavelet Neural Networks For Solving Ordinary And Partial Differential Equations

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dc.contributor.authorTan Lee Sen
dc.date.accessioned2024-01-22T02:10:06Z
dc.date.available2024-01-22T02:10:06Z
dc.date.issued2022-10
dc.description.abstractDifferential equations (DEs) have been widely used for modelling countless studies and applications in various disciplines. In recent years, artificial neural networks (ANNs) have gained attention in solving DEs in a more efficient way to approximate solutions of DEs. In this thesis, wavelet neural networks (WNNs) were employed and programmed to solve ordinary differential equations (ODEs) and partial differential equations (PDEs).
dc.identifier.urihttps://erepo.usm.my/handle/123456789/18153
dc.subjectImproved Training Method For Wavelet Neural Networks
dc.subjectSolving Ordinary And Partial Differential Equations
dc.titleAn Improved Training Method For Wavelet Neural Networks For Solving Ordinary And Partial Differential Equations
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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