Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus

Applied Microbiology and Biotechnology

Volumn 85, Issue 3, 2010, Pages 703-712

  Schubert, Mark ^a   Mourad, Safer ^a   Schwarze, Francis ^a  

^a SWISS FEDERAL LABORATORIES FOR MATERIALS SCIENCE AND TECHNOLOGY   (Switzerland)

Author keywords

Growth rate; Neolentinus lepideus; Physisporinus vitreus; Radial basis function neural network; Response surface model

Indexed keywords

DATA SETS; ENVIRONMENTAL CONDITIONS; EXPERIMENTAL DATA; EXPERIMENTAL FACTORS; FUNGAL GROWTH; GRAPHICAL PLOTS; KEY DETERMINANTS; NEOLENTINUS LEPIDEUS; QUADRATIC RESPONSE; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NETWORK; RBF NEURAL NETWORK; SPECIFIC GROWTH RATE; STATISTICAL INDICES; WATER ACTIVITY;

ATTITUDE CONTROL; BIODEGRADATION; FUNCTION EVALUATION; FUNGI; GROWTH RATE; NEURAL NETWORKS; RAPID SOLIDIFICATION; SENSITIVITY ANALYSIS; STATISTICAL METHODS; SURFACE PROPERTIES; WATER ANALYSIS;

RADIAL BASIS FUNCTION NETWORKS;

WATER;

BIOTECHNOLOGY; DATA SET; FUNGUS; GROWTH RATE; PH; RESPONSE ANALYSIS; SENSITIVITY ANALYSIS; TEMPERATURE EFFECT;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; BASIDIOMYCETES; ENVIRONMENTAL FACTOR; ENVIRONMENTAL TEMPERATURE; FUNGUS GROWTH; GROWTH RATE; NEOLENTINUS LEPIDEUS; NONHUMAN; NUCLEOTIDE SEQUENCE; PH; PHYSISPORINUS VITREUS; PREDICTION; RADIAL BASED FUNCTION; SENSITIVITY ANALYSIS;

BASIDIOMYCOTA; DNA, FUNGAL; HYDROGEN-ION CONCENTRATION; INDUSTRIAL MICROBIOLOGY; MODELS, THEORETICAL; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); SEQUENCE ANALYSIS, DNA; TEMPERATURE; WATER;

BASIDIOMYCOTA; FUNGI; NEOLENTINUS LEPIDEUS; PHYSISPORINUS;

EID: 74149084254     PISSN: 01757598     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00253-009-2185-3     Document Type: Article

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