Neural network and Monte Carlo simulation approach to investigate variability of copper concentration in phytoremediated contaminated soils

Journal of Environmental Management

Volumn 129, Issue , 2013, Pages 134-142

  Hattab, Nour ^a   Hambli, Ridha ^b   Motelica Heino, Mikael ^a   Mench, Michel ^c  

^a UNIVERSITÉ D'ORLÉANS   (France)

^b Prisme Institute MMH 8   (France)

^c UMR 1202 BIOGECO   (France)

Author keywords

Artificial neural network; Bean leaves; Copper; Monte Carlo simulation; Soil contamination; Soil factors variability

Indexed keywords

CONTAMINATION; COPPER; DECISION MAKING; FACTOR ANALYSIS; INTELLIGENT SYSTEMS; MONTE CARLO METHODS; SENSITIVITY ANALYSIS; SOIL POLLUTION; SOILS; STOCHASTIC SYSTEMS;

BEAN LEAF; CONTAMINATED SOILS; COPPER CONCENTRATION; MONTE CARLO'S SIMULATION; SOIL CONTAMINATION; SOIL FACTOR VARIABILITY; SOIL FACTORS; SOIL PARAMETERS; SOIL PROPERTY; STOCHASTICS;

NEURAL NETWORKS;

COPPER; DISSOLVED ORGANIC MATTER;

ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); COPPER; DECISION MAKING; LEAF; MONTE CARLO ANALYSIS; PARAMETERIZATION; SIMULATION; SOIL POLLUTION; SOIL PROPERTY; STOCHASTICITY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONCENTRATION (PARAMETERS); MONTE CARLO METHOD; PH; SOIL AMENDMENT; SOIL MOISTURE; SOIL POLLUTION; SOIL TREATMENT;

ARTIFICIAL NEURAL NETWORK; BEAN LEAVES; COPPER; MONTE CARLO SIMULATION; SOIL CONTAMINATION; SOIL FACTORS VARIABILITY;

BIODEGRADATION, ENVIRONMENTAL; COPPER; ENVIRONMENTAL MONITORING; ENVIRONMENTAL POLLUTION; ENVIRONMENTAL REMEDIATION; FRANCE; MODELS, THEORETICAL; MONTE CARLO METHOD; NEURAL NETWORKS (COMPUTER); SOIL POLLUTANTS; STOCHASTIC PROCESSES;

EID: 84881255518     PISSN: 03014797     EISSN: 10958630     Source Type: Journal    
DOI: 10.1016/j.jenvman.2013.07.003     Document Type: Article

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