Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches

Environmental Science and Pollution Research

Volumn 20, Issue 4, 2013, Pages 2271-2287

  Singh, Kunwar P ^a   Gupta, Shikha ^a   Ojha, Priyanka ^a   Rai, Premanjali ^a  

^a CSIR INDIAN INSTITUTE OF TOXICOLOGY RESEARCH   (India)

Author keywords

Adsorptive removal efficiency; Artificial intelligence; Artificial neural networks; Gene expression programming; Nonlinear models; Support vector machines

Indexed keywords

ADSORPTION; AQUEOUS SOLUTION; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CHLOROPHENOL; EXPERIMENTAL STUDY; FRUIT; GENETIC ALGORITHM; NONLINEARITY; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PH; POLLUTANT REMOVAL; PREDICTION; REGRESSION ANALYSIS; SHELL;

EID: 84875551049     PISSN: 09441344     EISSN: 16147499     Source Type: Journal    
DOI: 10.1007/s11356-012-1102-y     Document Type: Article

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