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ABSTRACT

Advanced Probabilistic Neural Network for the Prediction of Concrete Strength

Doo Kie Kim1, Seong Kyu Chang1, Sang Kil Chang1

Department of Civil and Environmental Engineering, Kunsan National University, Miryong, Kunsan, Jeonbuk, Korea

The International Conference on Computational & Experimental Engineering and Sciences 2007, 2(1), 29-34. https://doi.org/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 in the estimation results. In addition, the probability density function (PDF) is the sum of homogeneous multivariate Gaussian distribution because only one global smoothing parameter is used. The APNN was applied to predict the compressive strength of concrete using actual test data from two concrete companies, and the estimated results of APNN were compared with those of PNN. APNN showed better results than PNN in predicting the compressive strength of concrete and provided the promising probabilistic viewpoints by using the individual standard deviation in a variable.

Cite This Article

APA Style
Kim, D.K., Chang, S.K., Chang, S.K. (2007). Advanced probabilistic neural network for the prediction of concrete strength. The International Conference on Computational & Experimental Engineering and Sciences, 2(1), 29-34. https://doi.org/10.3970/icces.2007.002.029
Vancouver Style
Kim DK, Chang SK, Chang SK. Advanced probabilistic neural network for the prediction of concrete strength. Int Conf Comput Exp Eng Sciences . 2007;2(1):29-34 https://doi.org/10.3970/icces.2007.002.029
IEEE Style
D.K. Kim, S.K. Chang, and S.K. Chang, “Advanced Probabilistic Neural Network for the Prediction of Concrete Strength,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 2, no. 1, pp. 29-34, 2007. https://doi.org/10.3970/icces.2007.002.029



cc Copyright © 2007 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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