Apr 22, 2022 · We present a fuzzy deep wavelet neural network (FDWNN) inversion method trained by an accelerated hybrid learning algorithm to invert resistivity data of ERI.
Electrical resistivity imaging (ERI) is a non-invasive imaging technique for measuring resistivity, and the inversion problem of ERI is non-linear and ...
Electrical resistivity imaging (ERI) is a non-invasive imaging technique for measuring resistivity, and the inversion problem of ERI is non-linear and ...
Fuzzy deep wavelet neural network with hybrid learning algorithm: Application to electrical resistivity imaging inversion. https://doi.org/10.1016/j.knosys ...
Fuzzy deep wavelet neural network with hybrid learning algorithm: Application to electrical resistivity imaging inversion. Article. Jan 2022; KNOWL-BASED SYST.
Fuzzy deep wavelet neural network with hybrid learning algorithm: Application to electrical resistivity imaging inversion. Article. Jan 2022; KNOWL-BASED SYST.
Fuzzy deep wavelet neural network with hybrid learning algorithm: Application to electrical resistivity imaging inversion. Li Dong, Feibo Jiang, Minjie Wang ...
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In order to obtain high-quality electrical resistivity imaging (ERI) inversion results, this paper proposes a wavelet-based neural network inversion method.
Missing: Fuzzy deep
Dong, Fuzzy deep wavelet neural network with hybrid learning algorithm: application to electrical resistivity imaging inversion, Knowl.-Based Syst., № 242
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