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dc.contributor.authorallOsman, O.; Istanbul Commerce University, Eminonu, Istanbul, Turkeyen
dc.contributor.authorallMuhittin Albora, A.; Istanbul University, Engineering Faculty, Geophysical Department, Avcilar, Istanbul, Turkeyen
dc.contributor.authorallUcan, O. N.; Istanbul University, Engineering Faculty, Electrical & Electronics Dept, Avcilar, Istanbul, Turkeyen
dc.description.abstractThis paper presents a new approach for interpretation of residual gravity anomaly profiles, assuming horizontal cylinders as source. The new method, called Forced Neural Network (FNN), is introduced to determine the underground structure parameters which cause the anomalies. New technologies are improved to detect the borders of geological bodies in a reliable way. In a first phase one neuron is used to model the system and a back propagation algorithm is applied to find the density difference. In a second phase, density differences are quantified and a mean square error is computed. This process is iterated until the mean square error is small enough. After obtaining reliable results in the case of synthetic data, to simulate real data, the real case of the Gulf of Mexico gravity anomaly map, which has the form of anticline structure, is examined. Gravity anomaly values from a cross section of this real case, result to be very close to those obtained with the proposed method.en
dc.relation.ispartofseries6/49 (2006)en
dc.subjectForced Neural Networken
dc.subjectgravity anomalyen
dc.subjectsynthetic modelen
dc.subjectGulf of Mexicoen
dc.titleA new approach for residual gravity anomaly profile interpretations: Forced Neural Network (FNN)en
dc.subject.INGV04. Solid Earth::04.03. Geodesy::04.03.04. Gravity anomaliesen
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dc.description.journalTypeJCR Journalen
dc.contributor.authorOsman, O.en
dc.contributor.authorMuhittin Albora, A.en
dc.contributor.authorUcan, O. N.en
dc.contributor.departmentIstanbul Commerce University, Eminonu, Istanbul, Turkeyen
dc.contributor.departmentIstanbul University, Engineering Faculty, Geophysical Department, Avcilar, Istanbul, Turkeyen
dc.contributor.departmentIstanbul University, Engineering Faculty, Electrical & Electronics Dept, Avcilar, Istanbul, Turkeyen
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item.grantfulltextopen- Commerce University, Eminonu, Istanbul, Turkey- University, Engineering Faculty, Geophysical Department, Avcilar, Istanbul, Turkey- University, Engineering Faculty, Electrical & Electronics Dept, Avcilar, Istanbul, Turkey-
crisitem.classification.parent04. Solid Earth-
Appears in Collections:Annals of Geophysics
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