Use of artificial neural networks and genetic algorithms for prediction of sorption of an azo-metal complex dye onto lentil straw

Bioresource Technology

Volumn 129, Issue , 2013, Pages 396-401

  Çelekli, Abuzer ^a   Bozkurt, Hüseyin ^a   Geyik, Faruk ^a  

^a GAZIANTEP UNIVERSITY   (Turkey)

Author keywords

Artificial neural network (ANN); Gene expression programming (GEP); Lanaset Red G; Lentil straw; Sorption

Indexed keywords

FORECASTING; METAL COMPLEXES; NEURAL NETWORKS; PARTICLE SIZE;

ADSORBENT PARTICLE; COEFFICIENT VALUES; CONTACT TIME; DYE UPTAKE; ECO-FRIENDLY PROCESS; GENE EXPRESSION PROGRAMMING; INITIAL DYE CONCENTRATION; LANASET RED G; LOW-COST ADSORBENTS; NEURAL NETWORKS AND GENETIC ALGORITHMS; REMOVAL EFFICIENCIES; SECOND ORDER KINETICS; SINGLE EQUATION; SORPTION KINETICS; SORPTION PROCESS;

SORPTION;

AZO DYE; METAL COMPLEX;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; DYE; ERROR CORRECTION; GENE EXPRESSION; REMOVAL EXPERIMENT; SORPTION; STRAW;

ABSORPTION; ADSORPTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOSORPTION; COST; GENE EXPRESSION; GENETIC ALGORITHM; GENETIC MODEL; LENTIL; PARTICLE SIZE; PH; PREDICTION; PRIORITY JOURNAL; STRAW; WASTE COMPONENT REMOVAL;

EID: 84871408178     PISSN: 09608524     EISSN: 18732976     Source Type: Journal    
DOI: 10.1016/j.biortech.2012.11.085     Document Type: Article

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