Application of RBF neural network and ANFIS on the prediction of corrosion rate of pipeline steel in soil

Lecture Notes in Electrical Engineering

Volumn 124 LNEE, Issue VOL. 1, 2012, Pages 639-644

  He, San ^a   Zou, Yongli ^a   Quan, Desheng ^b   Wang, Hanyi ^a  

^a SOUTHWEST PETROLEUM UNIVERSITY   (China)

^b PetroChina Southwest Oil and Gas Field Company   (China)

Author keywords

ANFIS; pipeline steel; prediction; RBF neural network; soil corrosion

Indexed keywords

ADAPTIVE NEURAL FUZZY INFERENCE SYSTEMS; ANFIS; CORROSION TESTS; LABORATORY DATUM; PIPELINE STEEL; PREDICTION PRECISION; RBF NEURAL NETWORK; SOIL CORROSION;

COMPUTER SCIENCE; CORROSION RATE; FORECASTING; NEURAL NETWORKS; SOILS; STEEL PIPE;

RADIAL BASIS FUNCTION NETWORKS;

EID: 84875790233     PISSN: 18761100     EISSN: 18761119     Source Type: Book Series    
DOI: 10.1007/978-3-642-25781-0_93     Document Type: Conference Paper

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