Strength Prediction Model of High Strength Fly Ash Concrete Based On Mixed Kernel Function

Abstract

In this paper, the proportion of fly ash in cementitious material, the amount of cementitious material and the ratio of water to cement are selected, and the rough set theory is used to process the data. A mixed kernel function support vector machine prediction model with conditional attribute as input and decision attribute as output is established to explore the influence of three factors on the strength of high strength fly ash concrete. The prediction model with high prediction accuracy is selected for optimization. According to the existing test data, the variation law of concrete strength with proportioning parameters is summarized.