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Computers and Concrete
  Volume 22, Number 4, October 2018 , pages 355-363
DOI: https://doi.org/10.12989/cac.2018.22.4.355
 


Concrete compressive strength prediction using the imperialist competitive algorithm
Lukasz Sadowski, Mehdi Nikoo and Mohammad Nikoo

 
Abstract
    In the following paper, a socio-political heuristic search approach, named the imperialist competitive algorithm (ICA) has been used to improve the efficiency of the multi-layer perceptron artificial neural network (ANN) for predicting the compressive strength of concrete. 173 concrete samples have been investigated. For this purpose the values of slump flow, the weight of aggregate and cement, the maximum size of aggregate and the water-cement ratio have been used as the inputs. The compressive strength of concrete has been used as the output in the hybrid ICA-ANN model. Results have been compared with the multiple-linear regression model (MLR), the genetic algorithm (GA) and particle swarm optimization (PSO). The results indicate the superiority and high accuracy of the hybrid ICA-ANN model in predicting the compressive strength of concrete when compared to the other methods.
 
Key Words
    computer modeling; concrete; concrete structures; construction materials; non-destructive tests (NDT); reinforced concrete (RC)
 
Address
Lukasz Sadowski: Faculty of Civil Engineering, Wroc
 

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