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Volumn 277, Issue 1-3, 2011, Pages 348-355
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A comparison between semi-theoretical and empirical modeling of cross-flow microfiltration using ANN
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Author keywords
Artificial neural networks; Bovine serum albumin; Classic mechanisms of fouling; Cross flow microfiltration
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Indexed keywords
ARTIFICIAL NEURAL NETWORK;
BOVINE SERUM ALBUMINS;
CELLULOSE ESTERS;
CLASSIC MECHANISM;
CROSSFLOW MICROFILTRATION;
CROSSFLOW VELOCITIES;
EMPIRICAL MODELING;
FEED FORWARD;
FILTRATION TIME;
FLUX DECLINE;
HYDROPHOBIC MEMBRANE;
MEMBRANE FILTRATION SYSTEM;
MEMBRANE PORE SIZE;
MEMBRANE REJECTION;
MICROFILTRATION SYSTEMS;
MODELING TECHNIQUE;
NETWORK STRUCTURES;
OPERATING CONDITION;
OPERATING PARAMETERS;
POLYETHERSULFONES;
PORE BLOCKING;
PORE DIAMETERS;
PROCESSING TIME;
PROTEIN SOLUTION;
SEMI-EMPIRICAL;
SEMIEMPIRICAL MODELS;
TRAINING ALGORITHMS;
TRANSMEMBRANE PRESSURES;
BODY FLUIDS;
ESTERS;
ETHERS;
MEMBRANES;
NEURAL NETWORKS;
PH EFFECTS;
PRESSURE EFFECTS;
MICROFILTRATION;
ARTIFICIAL NEURAL NETWORK;
EMPIRICAL ANALYSIS;
FILTRATION;
FOULING;
HYDROPHOBICITY;
NUMERICAL MODEL;
PH;
PROTEIN;
TEMPERATURE;
BOVINAE;
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EID: 79960193540
PISSN: 00119164
EISSN: None
Source Type: Journal
DOI: 10.1016/j.desal.2011.04.057 Document Type: Article |
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Times cited : (44)
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References (19)
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