Modeling of the adsorptive removal of arsenic: A statistical approach

Journal of Environmental Chemical Engineering

Volumn 2, Issue 1, 2014, Pages 585-597

  Roy, P ^a   Mondal, N K ^a   Das, K ^a  

^a UNIVERSITY OF BURDWAN   (India)

Author keywords

Arsenic removal; Artificial neural network model; Central composite design; Fe SCC adsorbent; Response surface methodology

Indexed keywords

ADSORPTION; ARSENIC; NEURAL NETWORKS; OPTIMIZATION; POLLUTION CONTROL; REUSABILITY; SURFACE PROPERTIES; WATER POLLUTION;

ARSENIC IN DRINKING WATERS; ARSENIC REMOVAL; ARTIFICIAL NEURAL NETWORK MODELING; ARTIFICIAL NEURAL NETWORK MODELS; CENTRAL COMPOSITE DESIGNS; PREDICTIVE PERFORMANCE; REGENERATION EFFICIENCY; RESPONSE SURFACE METHODOLOGY;

CHEMICALS REMOVAL (WATER TREATMENT);

EID: 84897110436     PISSN: None     EISSN: 22133437     Source Type: Journal    
DOI: 10.1016/j.jece.2013.10.014     Document Type: Article

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