Artificial Neural Networks (ANNs) characterisation of soil pollution: The Polycyclic Aromatic Hydrocarbons (PAHs) case study

Comptes Rendus - Geoscience

Volumn 334, Issue 13, 2002, Pages 957-965

  Dan, Adrian ^a   Oosterbaan, Jasha ^a   Jamet, Philippe ^a  

^a PSL RESEARCH UNIVERSITY   (France)

Author keywords

Artificial Neural Networks (ANN); Coking plant; Manufactured gas plant; Polycyclic Aromatic Hydrocarbons (PAH); Soil contamination

Indexed keywords

ARTIFICIAL NEURAL NETWORK; PAH; SOIL POLLUTION;

EID: 0036811178     PISSN: 16310713     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1631-0713(02)01836-9     Document Type: Article

References (12)

1. Methods for detecting carcinogens and mutagens with the Salmonella/mammalian-microsome mutagenicity test
2. Polycyclic aromatic compounds in nature
3. Artificial neural networks for parameter estimation in geophysics
4. Identification of pollutants in soils of former coal industries by GC/MS and HPLC/MS
5. Organic compounds in Welsh soils: Polynuclear Aromatic Hydrocarbons
6. Environmental modification of PAH composition in coal tar containing samples
7. Priority polluants - A perspective view
8. Caractérisation de pollutions en HAP : Contribution de l'analyse exploratoire de données d'audit internationales
9. Polycyclic Aromatic Hydrocarbon composition and potential sources for sediment samples from the Beaufort and Barents Seas