Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/42613
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMiljanović, Miloš-
dc.contributor.authorNinkov, Toša-
dc.contributor.authorSušić, Zoran-
dc.contributor.authorTucikesic, Sanja-
dc.date.accessioned2017-08-11T06:38:44Z-
dc.date.available2017-08-11T06:38:44Z-
dc.date.issued2017-09-
dc.identifier.issn0975-1033 (Online); 0379-5136 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/42613-
dc.description1743-1750en_US
dc.description.abstractIn this paper, a method for evaluating and forecasting deformation movements present in buildings during tunneling works is described. The data used for processing is gathered from the project ’Prokop’ that has involved tunneling works under residential buildings, all mapped using a geodetic control network, or elevation network. Measurement results from this project are being used by the Finite Impulse Response (FIR) Neural Network as time series to predict future movements/deformations.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJMS Vol.46(09) [September 2017]en_US
dc.subjectGeodetic control networken_US
dc.subjectArtificial neural networken_US
dc.subjectFinite impulse responseen_US
dc.titleForecasting geodetic measurements using finite impulse response artificial neural networksen_US
dc.typeArticleen_US
Appears in Collections:IJMS Vol.46(09) [September 2017]

Files in This Item:
File Description SizeFormat 
IJMS 46(9) 1743-1750.pdf702.02 kBAdobe PDFView/Open


Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.