| Title |
Prediction of the Compressive Strength of Recycled Aggregate Concrete by Data Mining Technique |
| Authors |
Yoon Jie-Eon ; Kang Kyung-In |
| Keywords |
Artificial neural networks ; Regression analysis ; Concrete compressive strength ; Recycled concrete |
| Abstract |
Concrete recycling is one of the important subjects for sustainable development in these times. For the study of predicting the compressive strength of recycled aggregate concrete, this research used 525 results of compressive strength experiments of recycled aggregate concrete, which are executed for this paper. And this research compared multi-layer feed forward neural networks with regression analysis as data mining techniques to analyze the result data and compared the accuracy for each techniques. The neural network(NN) models give high prediction accuracy and research demonstrates that using NNs to predict the strength of recycled concrete is practical and appropriate |