Comparison between two types of Artificial Neural Networks used for validation of pharmaceutical processes

Powder Technology

Volumn 195, Issue 2, 2009, Pages 150-157

  Behzadi, Sharareh Salar ^a   Prakasvudhisarn, Chakguy ^b   Klocker, Johanna ^a   Wolschann, Peter ^a   Viernstein, Helmut ^a  

^a UNIVERSITY OF VIENNA   (Austria)

^b SHINAWATRA UNIVERSITY   (Thailand)

Author keywords

Bayesian neural network; Feed forward back propagation network; Granulation processes; Leave one out cross validation; Validation of pharmaceutical processes

Indexed keywords

ABSOLUTE ERROR; AIR PRESSURES; AIR VELOCITIES; ANGLE OF REPOSE; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; BATCH SIZES; BAYESIAN NEURAL NETWORK; BAYESIAN NEURAL NETWORKS; BED TEMPERATURE; CORRELATION COEFFICIENT; FEED MATERIALS; FEED-FORWARD BACK-PROPAGATION NETWORK; FEEDFORWARD BACKPROPAGATION; FLUID BED GRANULATION; GENERALIZED REGRESSION NEURAL NETWORKS; GRANULE PROPERTIES; INPUT VARIABLES; LEAVE-ONE-OUT CROSS VALIDATION; MULTI LAYER PERCEPTRON; OUTPUT VALUES; OUTPUT VARIABLES; PHARMACEUTICAL PROCESS; PREDICTION ACCURACY; SPRAY RATES; VALIDATION OF PHARMACEUTICAL PROCESSES;

ATMOSPHERIC PRESSURE; BACKPROPAGATION; BAYESIAN NETWORKS; BINDERS; FLUIDIZATION; GRANULATION;

NEURAL NETWORKS;

ACCURACY; AIRFLOW; ARTICLE; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC PRESSURE; BACK PROPAGATION; BAYES THEOREM; BINDING KINETICS; CHEMICAL PROCEDURES; COMPUTER PREDICTION; CONTROLLED STUDY; FLOW RATE; FLUIDIZED BED; GRANULATION; INTERMETHOD COMPARISON; PERCEPTRON; PHARMACEUTICS; PROCESS TECHNOLOGY; QUALITATIVE ANALYSIS; TEMPERATURE; VALIDATION STUDY;

EID: 67650558726     PISSN: 00325910     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.powtec.2009.05.025     Document Type: Article

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