Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells

Journal of Hazardous Materials

Volumn 153, Issue 3, 2008, Pages 1288-1300

  Yetilmezsoy, Kaan ^a   Demirel, Sevgi ^a  

^a YILDIZ TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Adsorption; Antep pistachio shells; Artificial neural networks; Modeling; Pb(II) removal

Indexed keywords

ADSORPTION; LEAD; METAL IONS; SOLUTIONS;

ADSORPTION EFFICIENCY; ANTEP PISTACHIO SHELLS;

NEURAL NETWORKS;

LEAD;

ADSORPTION; LEAD; METAL IONS; NEURAL NETWORKS; SOLUTIONS;

ADSORPTION; AQUEOUS SOLUTION; ARTIFICIAL NEURAL NETWORK; EVERGREEN TREE; EXPERIMENTAL STUDY; LEAD; MODELING; PH; PRINCIPAL COMPONENT ANALYSIS; REMOVAL EXPERIMENT;

ADSORPTION KINETICS; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; HEAVY METAL REMOVAL; PH; PISTACHIO; TEMPERATURE;

ADSORPTION; ALGORITHMS; HYDROGEN-ION CONCENTRATION; LEAD; NEURAL NETWORKS (COMPUTER); PISTACIA; SOLUTIONS; WASTE DISPOSAL, FLUID; WATER POLLUTANTS, CHEMICAL; WATER PURIFICATION;

PISTACIA VERA;

EID: 41449109567     PISSN: 03043894     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhazmat.2007.09.092     Document Type: Article

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