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Support vector machine, chaos theory, and particle swarm optimization are combined to build the prediction model of dam safety. The approaches are proposed to optimize the input and parameter of prediction model. First, the phase space reconstruction of prototype monitoring data series on dam behavior is implemented. The method identifying chaotic characteristics in monitoring data series is presented. Second, support vector machine is adopted to build the prediction model of dam safety. The characteristic vector of historical monitoring data, which is taken as support vector machine input, is extracted by phase space reconstruction. The chaotic particle swarm optimization algorithm is introduced to determine support vector machine parameters. A chaotic support vector machine-based prediction model of dam safety is built. Finally, the displacement behavior of one actual dam is taken as an example. The prediction capability on the built prediction model of dam displacement is evaluated. It is indicated that the proposed chaotic support vector machine-based model can provide more accurate forecasted results and is more suitable to be used to identify efficiently the dam behavior.

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During the operational period, unexpected upstream deformation has been observed in several super-high arch dams located in the alpine and gorge regions. In addition, the phenomenon of the downstream dam deformation monitoring values being apparently smaller than the numerical simulation results appears in some super-high arch dams. This paper focuses on the genetic mechanism of a super-high arch dam’s special deformation characteristics. The finite element method (FEM) was used to analyze the effects of solar radiation, valley contraction, and overhanging on super-high arch dam’s deformation behavior. First, the influences of solar radiation on the temperature field and deformation characteristics of the super-high arch dam under the shading effects of the mountain and the dam body were investigated. Second, the impacts of valley contraction on the deformation characteristics of the super-high arch dam during the storage period were studied. Subsequently, the impact of the overhanging effect on the super-high arch dam’s deformation was explored. Finally, a case study was conducted on the basis of the Jinping I super-high arch dam to evaluate the effectiveness of the proposed analytical method. It is indicated that the dam’s special deformation can be explained reasonably. Above all, in order to accurately analyze and predict the deformation characteristics of super high-arch dams in the alpine and gorge regions of Southwest China, solar radiation, valley contraction, and the dam-overhanging effect need to be considered as influencing factors of dam deformation.