建筑物非线性变形动态预测的数据机理:自记忆模型
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摘要
综合考虑建筑物沉降变形时间序列的单调增长的特殊性和非线性特征,利用动态数据反演建模方法和自记忆性方程,提出了一种随机与动力相结合的建筑物非线性变形预测的数据机理:自记忆模型.该方法将观测到的建筑物沉降位移时序数据视为描写建筑物变形非线性动力系统的特解,运用反演动力模式方法导出系统的微分方程,通过引入记忆函数,将制约动力系统的微分方程推演成一个差分-积分方程,从而建立建筑物沉降非线性变形预测的动力系统自记忆模型.由于该模型用历史资料估计记忆系数,蕴含了历史资料中对预测有用的信息,所以能很好地预测出系统极值,克服了以统计为基础的预报模型在做多步预测时预测值偏向平均值的缺点,较以往单一的确定论或随机统计论预测方法具有更高的拟合精度和预测准确率.将该方法用于实际工程建筑物沉降变形预测,证明了该模型的有效性及可行性.
引文
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