Artificial neural network for the evaluation of CO 2 corrosion in a pipeline steel

Journal of Solid State Electrochemistry

Volumn 13, Issue 5, 2009, Pages 773-780

  Bassam, A ^a   Ortega Toledo, D ^a   Hernandez, J A ^a   Gonzalez Rodriguez, J G ^a   Uruchurtu, J ^a  

^a UNIVERSIDAD AUTÓNOMA DEL ESTADO DE MORELOS   (Mexico)

Author keywords

Corrosion type prediction; Electrochemical impedance; Neural network

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; CORROSION TYPE PREDICTION; DATA SETS; DEVELOPED MODELS; ELECTROCHEMICAL IMPEDANCE; HIDDEN LAYERS; HYPERBOLIC TANGENT SIGMOID TRANSFER FUNCTIONS; IMPEDANCE CURVES; INHIBITOR CONCENTRATIONS; INPUT VARIABLES; LEVENBERG-MARQUARDT LEARNING ALGORITHMS; LINEAR TRANSFER FUNCTIONS; METAL SURFACES; NEURAL NETWORK; NYQUIST; PIPELINE STEELS; PREDICTIVE MODELS; RATE OF CORROSIONS; TRAINING DATA SETS;

BACKPROPAGATION; CORROSION; CORROSION INHIBITORS; CORROSION RATE; DAMAGE DETECTION; ELECTROCHEMICAL CORROSION; ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY; LEARNING ALGORITHMS; LEARNING SYSTEMS; PIPELINES; PROBABILITY DENSITY FUNCTION; STATISTICAL TESTS; STEEL; TRANSFER FUNCTIONS;

NEURAL NETWORKS;

EID: 60349104951     PISSN: 14328488     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10008-008-0588-1     Document Type: Article

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