Materials characterization by Inverse Neural Network approach

Carcangiu, S.;Fanni, A.;Montisci, A.;
2016-01-01

Abstract

An Inverse Neural Network approach is proposed to solve inverse problems in the field of material characterization in different electrical engineering applications. The flexibility and robustness of the inverse approach is demonstrated making reference to two different problems: the model identification of a magnetic material and the electric capacitance tomography of a polymeric material.
2016
Inglese
AEIT 2016 - International Annual Conference: Sustainable Development in the Mediterranean Area, Energy and ICT Networks of the Future
9788887237306
Institute of Electrical and Electronics Engineers Inc.
Carcangiu, S.
1
6
6
WOS:000402180500065
2-s2.0-85018459593
2016 AEIT International Annual Conference, AEIT 2016
Esperti anonimi
2016
ita
scientifica
Electric Capacitance Tomography; Inverse Models; Inverse problems; Material models parameter identification; Neural networks; Computer Networks and Communications; Hardware and Architecture; Energy Engineering and Power Technology; Renewable Energy, Sustainability and the Environment
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Carcangiu, S.; Fanni, A.; Montisci, A.; Cardelli, E.; Faba, A.; Quondam, S.
273
6
4.1 Contributo in Atti di convegno
none
info:eu-repo/semantics/conferencePaper
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