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Modeling of empty and full mold was made using both ANNs and RM. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Experiment was performed under vibration with the use of a computer-based data acquisition system. For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. This paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). Solution technique show versatile and powerful analysis capacity to solve various vibration problems includingīi-directionally stepped and plates on non-homogeneous elastic foundation. The solution can be stated as an extension of the so-calledĭiscrete parameter approach where the physical domain is broken down into discrete sub-domains, eachĮndowed with a response suitable for the purpose of mimicking problem at hand. This study is to extend analytical solutions of the discrete one-dimensional elements resting on elasticįoundation for solution of plate vibration problems. Where irregular boundaries or partial contact are encountered difficulties arise because it will be necessary toĭescribe the governing equation of motion in a general mathematical form. Plate vibration solutions have been available for regular geometries for a long time, but In engineering practice, beside static case often dynamic effects must be taken into consideration for