A comparative study for the concrete compressive strength estimation using neural network and neuro-fuzzy modelling approaches

Nondestructive Testing and Evaluation

Volumn 26, Issue 1, 2011, Pages 35-55

  Bilgehan, Mahmut ^a  

^a HARRAN UNIVERSITY   (Turkey)

Author keywords

ANFIS; ANN; compressive strength; ultrasonic pulse velocity

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS; ANFIS ARCHITECTURE; ANFIS MODEL; ANN; ARTIFICIAL NEURAL NETWORK MODELS; COMPARATIVE STUDIES; COMPRESSIVE STRENGTH OF CONCRETE; COMPUTATIONAL TIME; CONCRETE COMPRESSIVE STRENGTH; CONCRETE MIXTURE; CONCRETE STRENGTH; DENSITY VALUE; EXISTING REINFORCED CONCRETE; EXPERIMENTAL DATA; FEED-FORWARD; GAUSSIAN MEMBERSHIP FUNCTION; HEALTH MONITORING; LOSS OF ACCURACY; MANY CORE; MODEL ARCHITECTURE; NEURAL NET; NEURO-FUZZY; NEURO-FUZZY MODELLING; NON DESTRUCTIVE; REINFORCED CONCRETE STRUCTURES; STRUCTURAL ELEMENTS; ULTRASONIC PULSE VELOCITY;

BACKPROPAGATION ALGORITHMS; CONCRETE BUILDINGS; CONCRETE MIXERS; ESTIMATION; FUZZY INFERENCE; FUZZY SYSTEMS; LIGHT VELOCITY; MEMBERSHIP FUNCTIONS; NETWORK ARCHITECTURE; NEURAL NETWORKS; REINFORCED CONCRETE; STRUCTURAL HEALTH MONITORING; ULTRASONICS;

COMPRESSIVE STRENGTH;

EID: 79951816268     PISSN: 10589759     EISSN: 14772671     Source Type: Journal    
DOI: 10.1080/10589751003770100     Document Type: Article

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