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为分析深基坑在开挖过程中的变形规律,为安全生产提供有效信息,采用最小二乘支持向量机理论,利用粒子群算法对支持向量机的核参数进行优化,建立深基坑水平位移预测模型,并将预测结果与实际监测结果进行对比.研究结果表明:优化后的最小二乘支持向量机模型收敛速度快,泛化能力强,预测结果与实际监测数据有很好的一致性,精度高于传统的预测模型,对深基坑安全监控有一定的实用价值.
In order to analyze the deformation law of deep foundation pit during excavation and provide effective information for safety production, the least square support vector machine theory is used to optimize the kernel parameters of support vector machine by using particle swarm optimization algorithm. The horizontal displacement of deep foundation pit The prediction model is compared with the actual monitoring results.The results show that the optimized least squares support vector machine model has the advantages of fast convergence rate and generalization ability and the prediction results are in good agreement with the actual monitoring data, The accuracy is higher than the traditional prediction model, which has certain practical value for the safety monitoring of deep foundation pit.