【摘 要】
：
由于影响大坝监测数据因素多,且数据存在非等间距离散的情况,利用传统非等间距GM(1,1)模型的建模原理,分析了数据拟合与预测精度低的原因,提出了优化背景值的改进非等间距GM(
【机 构】
：
河海大学水文水资源与水利工程科学国家重点实验室,河海大学水利水电学院,江西省吉安市水文局,
论文部分内容阅读
由于影响大坝监测数据因素多,且数据存在非等间距离散的情况,利用传统非等间距GM(1,1)模型的建模原理,分析了数据拟合与预测精度低的原因,提出了优化背景值的改进非等间距GM(1,1)模型,根据两种模型对施工期堆石坝心墙的沉降观测数据进行拟合和预测。实例表明,改进模型精度较高,更接近观测值,可应用于工程实际中。
Due to many factors affecting the dam monitoring data and the data are scattered at irregular intervals, the reason of low accuracy of data fitting and prediction is analyzed by using the modeling principle of traditional non-equidistance GM (1,1) model. Optimize the non-equidistant GM (1,1) model of background value, and fit and predict the settlement data of core wall of rockfill dam during construction according to the two models. The examples show that the improved model is more accurate and closer to the observed value and can be applied in engineering practice.
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