Development of a multi-classification neural network model to determine the microbial growth/no growth interface

International Journal of Food Microbiology

Volumn 141, Issue 3, 2010, Pages 203-212

  Fernández Navarro, Francisco ^a   Valero, Antonio ^a   Hervás Martínez, César ^a   Gutiérrez, Pedro A ^a   García Gimeno, Rosa M ^a   Zurera Cosano, Gonzalo ^a  

^a UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Accuracy; Growth no growth interface; Imbalanced datasets; Memetic algorithm; Multi Classification; Oversampling method; S. aureus; Sensitivity; SMOTE

Indexed keywords

WATER;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION ALGORITHM; ENVIRONMENTAL FACTOR; FOOD CONTROL; FOOD MICROBIOTECHNOLOGY; FOOD SAFETY; GROWTH REGULATION; MATHEMATICAL MODEL; METHODOLOGY; MICROBIAL GROWTH; NONHUMAN; PARAMETER; PH; PROBABILITY; SAMPLING; SMOTE MEMETIC RADIAL BASIS FUNCTION; STAPHYLOCOCCUS AUREUS; TEMPERATURE SENSITIVITY; ALGORITHM; BIOLOGICAL MODEL; CHEMISTRY; GROWTH, DEVELOPMENT AND AGING; METABOLISM; TEMPERATURE;

ALGORITHMS; FOOD MICROBIOLOGY; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); STAPHYLOCOCCUS AUREUS; TEMPERATURE; WATER;

STAPHYLOCOCCUS AUREUS;

EID: 77954312094     PISSN: 01681605     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijfoodmicro.2010.05.013     Document Type: Article

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