Considering the limitations of the traditional hydraulic‐seasonal‐time (HST) model, this study proposes a hybrid modeling method for the deformation prediction of high concrete dams during the operational period. First, the elastic finite element (FE) method is applied to simulate the interactive effects of structural properties, topography, geology, and high hydrostatic load on the deformation behaviour of high concrete dams in operating conditions. The hybrid model of hydrostatic pressure deformation is established. The hybrid hydraulic‐seasonal‐time (HHST) model is proposed. Second, the self‐adaptive stochastic inertia weight, dynamic learning factors, and velocity and position parameters are introduced to improve the particle swarm optimization (PSO) algorithm. The hybrid prediction approach is developed through the comprehensive application of the HHST model and the improved PSO algorithm. The proposed methodology is adopted for the Jinping I project, which is the highest concrete arch dam in the world. The analysis results indicate that the model accuracy is good and that the model performance is promoted.

中文翻译：

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预测施工期高混凝土大坝变形特性的水力-季节-时间混合模型

考虑到传统的水文季节时间（HST）模型的局限性，本研究提出了一种混合模型方法，用于预测运营期高混凝土大坝的变形。首先，应用弹性有限元（FE）方法来模拟结构特性，地形，地质和高静水载荷对高混凝土大坝在运行条件下的变形行为的相互作用。建立了静水压力变形的混合模型。提出了混合水力-季节-时间（HHST）模型。其次，引入了自适应随机惯性权重，动态学习因子以及速度和位置参数，以改进粒子群优化（PSO）算法。通过对HHST模型和改进的PSO算法的综合应用，发展了混合预测方法。拟议的方法被世界上最高的混凝土拱坝锦屏一期工程采用。分析结果表明，模型精度良好，提高了模型性能。