Volterra级数混沌自适应模型在变形分析中的应用  

Application of Volterra Series Chaos Adaptive Model in Deformation Analysis

作　　者：彭磊 PENG Lei(Power China Hebei Electric Power Design&Research Institute Co.,Ltd.,Shijiazhuang 050031,China)

机构地区：[1]中国电建集团河北省电力勘测设计研究院有限公司,河北石家庄050031

出　　处：《测绘与空间地理信息》2024年第3期206-208,共3页Geomatics & Spatial Information Technology

摘　　要：针对变形监测数据混沌序列的特点,提出一种基于Volterra级数的混沌时间序列变形预测模型。经过相空间重构,确定合适的嵌入维数和延迟时间,输入Volterra级数自适应预测模型,然后得到变形量的预测值。将预测值与实际值及其他预测模型的预测结果进行比较,发现基于Volterra级数的混沌时间序列预测模型精度较高,在变形预测上是可行的。According to the characteristics of chaotic time series of deformation monitoring data,a deformation prediction model of chaotic time series based on Volterra series is proposed.After phase space reconstruction,the suitable embedding dimension and delay time are determined,and the adaptive prediction model of Volterra series is input,then the prediction value of deformation quantity is obtained.By comparing the predicted value with the actual value and the prediction results of other prediction models,it is found that the chaotic time series prediction model based on Volterra series has higher accuracy and is feasible in deformation prediction.

关 键 词：VOLTERRA级数 混沌时间序列 变形预测 

分 类 号：P209[天文地球—测绘科学与技术]