Prediction of the concrete compressive strength by means of core testing using GMDH-type neural network and ANFIS models

Computational Materials Science

Volumn 51, Issue 1, 2012, Pages 261-272

  Madandoust, Rahmat ^a   Bungey, John H ^b   Ghavidel, Reza ^a  

^a UNIVERSITY OF GUILAN   (Iran)

^b UNIVERSITY OF LIVERPOOL   (United Kingdom)

Author keywords

ANFIS; Compressive strength; Core test; Genetic algorithm (GA); GMDH type neural network

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; AGGREGATE SIZE; ANFIS; ANFIS MODEL; CONCRETE AGE; CONCRETE COMPRESSIVE STRENGTH; CORE DIAMETERS; CORE TEST; CORE TESTING; CUBE STRENGTH; GMDH-TYPE NEURAL NETWORKS; GROUP METHOD OF DATA HANDLING; HARDENED CONCRETE; IN-SITU CONCRETE; INPUT PARAMETER; LENGTH TO DIAMETER RATIO; MODEL OUTPUTS; OPTIMAL DESIGN;

ABILITY TESTING; CONCRETE TESTING; DATA HANDLING; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; GENETIC ALGORITHMS; SENSITIVITY ANALYSIS; SINGULAR VALUE DECOMPOSITION;

COMPRESSIVE STRENGTH;

EID: 80052036795     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2011.07.053     Document Type: Article

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