Advanced Probabilistic Neural Network for the Prediction of Concrete Strength
Doo Kie Kim1, Seong Kyu Chang1, Sang Kil Chang1
The International Conference on Computational & Experimental Engineering and Sciences, Vol.2, No.1, pp. 29-34, 2007, DOI:10.3970/icces.2007.002.029
Abstract Accurate and realistic strength estimation before the placement of concrete is highly desirable. In this study, the advanced probabilistic neural network (APNN) was proposed to reflect the global probability density function by summing the heterogeneous local probability density function automatically determined in the individual standard deviation of variables. Currently, the estimation of the compressive strength of concrete is performed by a probabilistic neural network (PNN) on the basis of concrete mix proportions, and the PNN is improved by the iteration method. However, an empirical method has been incorporated to specify the smoothing parameter in the PNN technique, causing significant uncertainty… More >