Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN

Measurement: Journal of the International Measurement Confederation

Volumn 57, Issue , 2014, Pages 122-131

  Momeni, E ^a   Nazir, R ^a   Jahed Armaghani, D ^a   Maizir, H ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

Author keywords

Artificial neural network; Dynamic load test; Genetic algorithm; Pile bearing capacity

Indexed keywords

ALGORITHMS; BEARING CAPACITY; DYNAMIC LOADS; FORECASTING; GENETIC ALGORITHMS; GLOBAL OPTIMIZATION; LOAD TESTING; NETWORK ARCHITECTURE; NEURAL NETWORKS; PRECAST CONCRETE; STATISTICAL TESTS; MEAN SQUARE ERROR; SENSITIVITY ANALYSIS;

COEFFICIENT OF DETERMINATION; GENETIC-ALGORITHM OPTIMIZATIONS; GEOMETRICAL PROPERTY; PILE BEARING; PREDICTIVE MODELING; RATE OF CONVERGENCE; TRIAL-AND-ERROR METHOD; ULTIMATE BEARING CAPACITY; HYBRID GENETIC ALGORITHMS;

PILES;

EID: 84906825852     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2014.08.007     Document Type: Article

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