基于进化支持向量机的单桩竖向极限承载力的预测

PREDICTION OF VERTICAL ULTIMATE BEARING CAPACITY OF SINGLE PILE BASED ON GENETIC ALGORITHM AND SUPPORT VECTOR MACHINE

通过将改进遗传算法与支持向量机相结合,建立一种用于单桩竖向极限承载力预测的进化支持向量机模型。这种方法基于实测数据,利用遗传算法搜索最优的支持向量机参数,用获得的最优模型进行学习,从而得到泛化能力更好的预测模型。结果表明,该算法可以有效地解决支持向量机的参数确定问题,给出的算例结果是令人满意的。

The prediction model of vertical ultimate bearing capacity of single pile is built by combining improved genetic algorithm and support vector regression machine. The practical data are used to train the support vector machine whose parameters are determined in global optimization by improved genetic algorithm. Thus, a prediction model with better generalizing capacity is built. The study shows that this method is effective for determining the parameters of support vector machine, and the results are satisfactory.