CAJ | 학술논문

为了克服神经网络以及单输出支持向量回归算法在有限元模型修正中的不足,提出了基于多输出支持向量回归算法的有限元模型修正方法.根据5-折交叉验证法选择支持向量回归机的参数,用均匀试验设计法构造样本,联合结构的动力和静力响应数据作为输入,多个设计参数作为输出,以支持向量回归机逼近输入输出二者之间的非线性映射关系,然后利用支持向量回归机的泛化推广能力,求解设计参数的目标值.空间网格结构数值模型的分析结果表明,该方法能同时修正多个设计参数,在少量样本的情况下具有较高的修正精度,为有限元模型修正提供了一种新的探索.
위료극복신경망락이급단수출지지향량회귀산법재유한원모형수정중적불족,제출료기우다수출지지향량회귀산법적유한원모형수정방법.근거5-절교차험증법선택지지향량회귀궤적삼수,용균균시험설계법구조양본,연합결구적동력화정력향응수거작위수입,다개설계삼수작위수출,이지지향량회귀궤핍근수입수출이자지간적비선성영사관계,연후이용지지향량회귀궤적범화추엄능력,구해설계삼수적목표치.공간망격결구수치모형적분석결과표명,해방법능동시수정다개설계삼수,재소량양본적정황하구유교고적수정정도,위유한원모형수정제공료일충신적탐색.
In order to overcome the shortcomings in finite element model updating by means of traditional neural network and single-output support vector regression, a new method based on multiple-outputs support regression algorithm was proposed. The parameters of support vector regression were selected according to 5-fold cross validation, the uniform design method was used to construct the samples, the static and dynamic response data were taken as the inputs and a number of design parameters as the outputs, the support vector regression machine was applied to approximate the mapping relationship between the inputs and outputs, and then the generalization ability of the support vector regression machine was utilized to get the target values of the design parameters. The result of numerical application to a space grid structure shows that: the method proposed can update a number of design parameters with high precision in the case of a small number of samples. It provides a new exploration for finite element model updating.