Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network

Expert Systems with Applications

Volumn 38, Issue 8, 2011, Pages 9609-9618

  Atici, U ^a  

^a NIGDE UNIVERSITY   (Turkey)

Author keywords

Admixture concrete; Artificial neural network; Compressive strength; Multiple regression analysis

Indexed keywords

ADMIXTURE CONCRETE; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; BLAST FURNACE SLAGS; CLASSICAL METHODS; COMPRESSIVE STRENGTH OF CONCRETE; CONCRETE MIXTURE; FUNCTIONAL RELATIONSHIP; MINERAL ADMIXTURES; MULTIPLE REGRESSION ANALYSIS; MULTIVARIABLE REGRESSION ANALYSIS; NON DESTRUCTIVE TESTING; REBOUND NUMBER; ULTRASONIC PULSE VELOCITY;

BLAST FURNACES; COMPRESSIVE STRENGTH; CONCRETE ADDITIVES; CONCRETE TESTING; CURING; FLY ASH; FORECASTING; FURNACES; GAS BURNERS; INVERSE PROBLEMS; METAL ANALYSIS; METAL REFINERIES; METALLURGICAL FURNACES; NONDESTRUCTIVE EXAMINATION; REGRESSION ANALYSIS; SLAGS; STATISTICS;

NEURAL NETWORKS;

EID: 79953730262     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.01.156     Document Type: Article

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