A concrete dam deformation forecasting model is established based on the particle swarm optimization (PSO) algorithm and the traditional multi-statistical regression model.
将粒子群算法引入大坝安全监控领域，并结合多元回归统计模型，建立基于粒子群算法的混凝土坝变形预报模型。
Time series analysis method is a main method by which deformation forecasting model is established in deformation measurements.
时间序列分析方法是建立变形测量预测模型的主要方法。
Aiming at the disadvantages of experience formula, the case-based SVM method for maximal deformation forecasting of surrounding rocks of tunnels is proposed.
针对经验公式方法的不足，提出基于工程实例的隧洞最大允许变形的支持向量机(SVM)自动获取方法。
The practice shows that deformation forecasting value can be in good agreement with measured results, and that the model can be applied in monitoring for dam safety.
实践表明，变形预报值能很好地吻合了实测结果，表明该模型可以用于大坝安全监控。
The practice shows that deformation forecasting value can be in good agreement with measured results, and that the model can be applied in monitoring for dam safety.
实践表明，变形预报值能很好地吻合了实测结果，表明该模型可以用于大坝安全监控。
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