Prediction of copper and chromium concentrations in bean leaves based on an artificial neural network model

International Journal of Environmental Science and Technology

Volumn 11, Issue 6, 2014, Pages 1781-1786

  Hattab, N ^a,b,c   Hambli, R ^d  

^a UMR 7327   (France)

^b UNIVERSITÉ DE TOURS   (France)

^c DAMASCUS UNIVERSITY   (Syrian Arab Republic)

^d Institut PRISME/Equipe MMH   (France)

Author keywords

Artificial neural networks; Bean leaves; Copper chromium concentrations; Soil

Indexed keywords

CHROMIUM; COPPER; FORECASTING; MATHEMATICAL MODELS; NEURAL NETWORKS; PLANTS (BOTANY); SOILS;

ARTIFICIAL NEURAL NETWORK MODELING; BEAN LEAVES; CHROMIUM CONCENTRATION; CORRELATION COEFFICIENT; DISSOLVED ORGANIC CARBON; RELATIVE CONCENTRATION; SOIL AND PLANT ANALYSIS; SOIL ELECTRICAL CONDUCTIVITY;

SOIL SURVEYS;

ARTIFICIAL NEURAL NETWORK; CHROMIUM; CONCENTRATION (COMPOSITION); COPPER; CORRELATION; LEAF; POLLUTION MONITORING; SOIL ANALYSIS; SOIL PROPERTY; TOXICITY TEST;

EID: 84905975258     PISSN: 17351472     EISSN: 17352630     Source Type: Journal    
DOI: 10.1007/s13762-014-0496-0     Document Type: Article

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