基于鲸鱼算法优化支持向量机的刚构桥可靠度分析
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杨佳男(1995—), 男, 学士, 工程师, 从事桥梁安全评估及养护等方面的工作。

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U448.23

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Reliability Analysis of Rigid-frame Bridges Based on Whale Optimization Algorithm Support Vector Machine
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Jiujiu City Road and Transportation Management Center, Shaoxing 311800, China

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    摘要:

    针对刚构桥施工期可靠度分析中功能函数高度非线性、有限元计算耗时长的难题,提出一种基于鲸鱼算法优化支持向量机(WOA-SVM)的可靠度分析方法。以关键随机变量为输入,最大悬臂状态下关键截面的功能函数值为输出;利用WOA对SVM的惩罚因子、不敏感系数及核函数参数进行自适应全局寻优,建立WOA-SVM代理模型,并将其与蒙特卡洛法结合进行可靠度计算与敏感性分析。工程实例表明:优化后模型的预测精度显著优于默认参数组合;基于WOA-SVM的可靠指标为3.98,满足规范要求,与有限元结果相比失效概率相对误差仅4.8%;混凝土抗拉强度是影响施工期可靠度的首要因素,其次为混凝土容重和施工荷载。该方法可为同类桥梁施工安全评估提供参考。

    Abstract:

    Aiming at the problems of highly nonlinear functional functions and long time consumption in finite element calculation in the reliability analysis of rigid-frame bridges during construction period, a reliability analysis method based on the WOA?SVM is proposed. Key random variables are taken as the inputs, and the functional function value of the critical section at the maximum cantilever state is taken as the output. The WOA is employed to adaptively and globally optimize the penalty factor, insensitive coefficient and kernel function parameter of the SVM, thereby establishing a WOA?SVM surrogate model, which is then combined with the Monte Carlo method for reliability calculation and sensitivity analysis. An engineering example demonstrates that the prediction accuracy of the optimized model is significantly superior to the default parameter combination. The reliability index obtained by WOA?SVM is 3.98, satisfying the code requirement, and the relative error in failure probability is only 4.8% compared with the finite element results. Concrete tensile strength is identified as the primary factor affecting construction?stage reliability, followed by concrete density and construction load. The proposed method can provide a reference for the construction safety assessment of similar bridges.

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杨佳男.基于鲸鱼算法优化支持向量机的刚构桥可靠度分析[J].城市道桥与防洪,2026,(10):30-35.

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  • 收稿日期:2026-04-29
  • 最后修改日期:2026-05-05
  • 录用日期:2026-05-06
  • 在线发布日期: 2026-10-18
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