Using complex permittivity and artificial neural networks for contaminant prediction

Journal of Environmental Engineering

Volumn 128, Issue 8, 2002, Pages 740-747

  Lindsay, John B ^b   Shang, Julie Q ^a,b   Rowe, R Kerry ^a,c  

^a ASCE ^*

^b UNIVERSITY OF WESTERN ONTARIO   (Canada)

^c QUEEN S UNIVERSITY   (Canada)

Author keywords

Contaminants; Neural networks; Nondestructive tests; Prediction; Water quality

Indexed keywords

DATA ACQUISITION; ELECTROLYTES; IONS; NEURAL NETWORKS; POSITIVE IONS;

COMPLEX PERMITTIVITY;

ENVIRONMENTAL ENGINEERING;

ARTIFICIAL NEURAL NETWORK; ELECTROLYTE; GROUNDWATER POLLUTION; PERMITTIVITY; PREDICTION; WATER QUALITY;

EID: 0036685472     PISSN: 07339372     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-9372(2002)128:8(740)     Document Type: Article

References (22)

1. Bootstrapping confidence intervals for clinical input variable effects in a network trained to identify the presence of acute myocardial infarction
2. Analysis of solute transport behaviour in heterogeneous undisturbed soil cores using resistive electrical impedance tomography
3. Estimating construction productivity: Neural-network-based approach
4. Multicollinearity: A tale of two nonparametric regressions
5. Note on free lunches and cross-validation
6. Progress in supervised neural networks: What's new since Lippmann?
7. Dielectric properties of organic solute/water mixtures: Hydrophobic hydration and relaxation
8. Identification of contaminated soils by dielectric constant and electrical conductivity
9. Water: A dielectric reference
10. Dielectric properties of polyelectrolyte solutions
11. Measurement of the intrinsic properties of materials by time-domain techniques
12. Dielectric properties of aqueous NaCl solutions at microwave frequencies
13. Neural network-based screening for groundwater reclamation under uncertainty
14. Simulating structural analysis with neural network
15. Dielectric permittivity of soils mixed with organic and inorganic fluids