混凝土中锚杆锚固强度的SVM回归模型

锚杆锚固强度是评价锚杆锚固质量的主要因素之一,而混凝土中锚杆锚固强度受多因素影响,各因素间也具有复杂的关联。应用支持向量机回归原理,以混凝土龄期、锚杆直径和锚固长度3个因素作为输入列向量构建样本集,选用径向基核函数建立混凝土中锚杆锚固强度的支持向量机回归预测模型。利用30组锚固强度实验数据中2/3的数据作为训练样本,剩余1/3的数据作为预测样本,对锚固强度进行回归预测,将预测结果与试验结果和BP网络计算结果进行对比分析。研究结果表明:此模型预测精度高,具有良好的泛化能力,预测结果具有可信性,将SVM方法运用于混凝土中锚杆锚固强度的预测是合理有效的,为锚固强度的预测提供了一条新的途径。

Regression Model of Bolt Anchoring Strength in Concrete Based on SVM

As one of the main factors of evaluating the anchoring quality, bolt anchoring strength in the concrete is affected by many factors which have complex interrelationships with each other. Concrete age, bolt diameter and anchorage length are used as the input column vector to build sample set, and radial basis kernel function is adopted for an prediction model of bolt anchoring strength in concrete based on support vector machine for regression. There are 30 groups of experimental data of anchoring strength. Two-thirds of those groups are selected as training samples, and the others are selected as predicted samples to forecast anchorage strength. Then the predicted results are compared with the test result and BP network result. Comparison suggest that this model has high prediction accuracy and good generalization ability, and the prediction results are credible. It is reasonable and effective to apply SVM to predict the anchorage strength in concrete.