DocumentCode
3394773
Title
Identification of magnetic phases of weathered tuffite soil using artificial neural network
Author
De Souza, Paulo A., Jr. ; Garg, Vijayendra K.
Author_Institution
Dept. de Fisica, Univ. Fed. do Espirito Santo, Brazil
Volume
2
fYear
1997
fDate
3-6 Aug. 1997
Firstpage
1290
Abstract
Magnetic phases of weathering tuffite soil have been identified using Mossbauer parameters (I.S., Q.S., and Hn) and artificial neural networks (ANN). Reported Mossbauer parameters were stored in a computer data bank. These parameters were used to train an ANN called counterpropagation network (CPN). The ANN identified the phases to almost 100% correctness. The identification of magnetic phases by ANN indicate that it could be an alternative method in identification of magnetic phases of soils.
Keywords
Mossbauer spectroscopy; geophysical techniques; magnetic transitions; neural nets; soil; Mossbauer parameters; artificial neural network; counterpropagation network; magnetic phases; weathered tuffite soil; Artificial neural networks; Biology computing; Computer networks; Data mining; Equations; Least squares methods; Neurons; Soil; Transfer functions; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Print_ISBN
0-7803-3694-1
Type
conf
DOI
10.1109/MWSCAS.1997.662317
Filename
662317
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