摘要
Abstract
The current dam deformation forecast, based on the single forecast model, is unable to consider the condition of the number of sample data and the optimization of influencing factors. The Gray Model (GM) is appli-cable to short-term data and is easy to determine influencing factors. The support vector machine (SVM) is applica-ble to the forecast of long-term data, but cannot determine the best influencing factors. The combination of SVM and GM can achieve the objective of complementary model, and optimize influencing factors and precision of fit-ting and forecasting.关键词
灰色模型/支持向量机/预测/大坝变形Key words
GM/SVM/Forecast/Dam Deformation分类
天文与地球科学
