| Title |
Development of Prediction System of Concrete Strength using Neural-Network-based Model |
| Keywords |
Artificial Neural Network ; Prediction ; Concrete Strength ; Parameter Condensation ; Weighting Technique |
| Abstract |
The purpose of this paper is to develop the I-PreConS (Intelligent system for PREdiction of CONcrete Strength) that provides in-place strength information of the concrete to facilitate concrete form removal and scheduling for construction. For this purpose, the system is developed with artificial neural networks(ANN). ANN does not need a specific equation form compared with traditional prediction models. Instead of that, it needs enough input-output data. Also, it can continuously re-train the new data, so that it can conveniently adapt to new data. Various simulations are performed for the development of a more efficient ANN model. Two major techniqes are applied to increase the accuracy. One is to use parameter condensation technique in the determination of input neurons. The other is to introduce the weighting technique of input neurons for more prediction accuracy at the early stages of concrete curing period. This study shows that I-PreConS using ANN is very applicable to predict the concrete strength. |