Using complex permittivity and artificial neural networks to identify and classify copper, zinc, and lead contamination in soil

Canadian Geotechnical Journal

Volumn 43, Issue 1, 2006, Pages 100-109

  Amegashie, F ^a   Shang, J Q ^a   Yanful, E K ^a   Ding, W ^a   Al Martini, S ^a  

^a UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

Artificial neural networks; Complex permittivity; Contaminant detection; Heavy metals; Subsurface contamination

Indexed keywords

CONTAMINATION; COPPER; LEAD; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; PERMITTIVITY MEASUREMENT; ZINC;

COMPLEX PERMITTIVITY; CONTAMINANT DETECTION; SOIL CONTAMINATION; SUBSURFACE CONTAMINATION;

SOIL TESTING;

CONTAMINATION; COPPER; LEAD; NEURAL NETWORKS; NONDESTRUCTIVE EXAMINATION; PERMITTIVITY MEASUREMENT; SOIL TESTING; ZINC;

ARTIFICIAL NEURAL NETWORK; SOIL POLLUTION;

EID: 33644906366     PISSN: 00083674     EISSN: None     Source Type: Journal    
DOI: 10.1139/t05-085     Document Type: Article

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