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Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/3515
DC FieldValueLanguage
dc.contributor.authorallShimelevich, M. I.; Moscow State Geoprospecting University, Moscow, Russiaen
dc.contributor.authorallObornev, M. A.; Moscow State Geoprospecting University, Moscow, Russiaen
dc.contributor.authorallGavryushov, S.; Engelhardt Institute of Molecular Biology, Moscow, Russiaen
dc.date.accessioned2007-12-20T13:48:25Zen
dc.date.available2007-12-20T13:48:25Zen
dc.date.issued2007-02en
dc.identifier.urihttp://hdl.handle.net/2122/3515en
dc.description.abstractThe inverse MagnetoTelluric (MT) operator is approximated by means of the Neural Network (NN). The methodology of the NN interpretation in classes of the geoelectrical sections described by the hundreds of parameters is proposed. Error of the NN inversion and field misfit are evaluated. A rapid NN algorithm solving the inverse problem and detecting changes of time-dependent dynamic parameters of the section is applied to 2D synthetic data.en
dc.language.isoEnglishen
dc.relation.ispartofseries1/50 (2007)en
dc.subjectmagnetotelluric inverse problemen
dc.subjectneural networken
dc.subjectEM monitoringen
dc.titleRapid neuronet inversion of 2D magnetotelluric data for monitoring of geoelectrical section parametersen
dc.typearticleen
dc.type.QualityControlPeer-revieweden
dc.subject.INGV01. Atmosphere::01.03. Magnetosphere::01.03.06. Instruments and techniquesen
dc.relation.referencesPOULTON, M.M. (2002): Neural networks as an intelligence amplification tool: a review of applications, Geophysics, 67 (3), 979-993 RAICHE, A. (1991): A pattern recognition approach to geophysical inversion using neural nets, Geophys. J. Int., 105, 629-648. SHIMELEVICH, M.I. and E.A. OBORNEV (1999): The method of neural network applied to the approximation of the inverse operators in electromagnetic sounding problems, Izvestiya Vuzov (Geol. Prospect.), 2, 102-106 (in Russian). SHIMELEVICH, M.I., E.A. OBORNEV and S.A. GAVRYUSHOV (2001): A method of designing neural networks for solving multiparametric inverse problems of magnetotelluric sounding, Izvestiya Vuzov (Geol. Prospect.), 6, 129-137 (in Russian). SHIMELEVICH, M.I., E.A. OBORNEV and S.A. GAVRYUSHOV (2002): Neuronet approximation of the inverse MT operators for geoelectrical monitoring, in Proceedings of III International Workshop on Magnetic, Electric and Electromagnetic Methods in Seismology and Volcanlogy (MEEMSV-2002), September 3-6, Moscow, 59-62. SHIMELEVICH, M.I., E.A. OBORNEV and S.A. GAVRYUSHOV (2003): Application of neuronet approximation to the solution of geo-electromonitoring problems, Izvestiya Vuzov (Geol. Prospect.), 4, 70-71 (in Russian). SPICHAK, V. and I. POPOVA (2000): Artificial neural network inversion of magnetotelluric data in terms of three-dimensional Earth macroparameters, Geophys. J. Int., 142, 15-26. SPICHAK, V., K. FUKUOKA, T. KABAYASHI, T. MOGI, I. POPOVA and H. SHIMA (2002): ANN reconstruction of geoelectrical parameters of the Mionou fault zone by scalar CSAMT data, J. Appl. Geophys., 49, 75-90. ZHDANOV, M.S. and A. CHERNYAVSKIY (2004): Rapid threedimensional inversion of multi-transmitter electromagnetic data using the spectral Lanczos decomposition method, Inverse Problems, 20, S233-S256.en
dc.description.journalTypeJCR Journalen
dc.description.fulltextopenen
dc.contributor.authorShimelevich, M. I.en
dc.contributor.authorObornev, M. A.en
dc.contributor.authorGavryushov, S.en
dc.contributor.departmentMoscow State Geoprospecting University, Moscow, Russiaen
dc.contributor.departmentMoscow State Geoprospecting University, Moscow, Russiaen
dc.contributor.departmentEngelhardt Institute of Molecular Biology, Moscow, Russiaen
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptMoscow State Geoprospecting University, Moscow, Russia-
crisitem.author.deptMoscow State Geoprospecting University, Moscow, Russia-
crisitem.author.deptEngelhardt Institute of Molecular Biology, Moscow, Russia-
crisitem.classification.parent01. Atmosphere-
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