A Novel Prediction Method of Dynamic Wall Pressure for Silos Based on Support Vector Machine

Abstract

The physical properties and mechanical characteristics of storage materials are significantly different from those of ordinary solids and liquids. The distribution of dynamic wall pressure during silo discharge is quite complicated. Considering the nonlinear relationship between the factors which affect the dynamic lateral pressure of silos, a prediction method of dynamic wall pressure for silos based on support vector machine (SVM) is proposed here, and furthermore, the modified grid search method (GSM) is incorporated in obtaining the optimal support vector machine parameters to improve the accuracy of the prediction. Comparing the results of the proposed prediction model with the results of experiment methods and simulation methods, it can be found that the SVM prediction model shows high accuracy and high generalization ability, and the prediction results of the model fit well with the results of experiment and simulation methods. The proposed method can provide reference for the prediction of the dynamic wall pressure of silos.