本文首先略述用自回归模式去拟合平稳时间序列的各种方法；
The methods for fitting the autoregressive model to the stationary time series are briefly reviewed.
实例研究表明，基于参数优化的自记忆模型提高了自记忆模型的适应性，具有更好的拟合、预测效果。
The example showed that self-memory model, based on parameter optimization, advanced the adaptability and had a better fitting effect and prediction effect.
在实验基础上建立结构受载时标准样本特征向量数据库。根据最小二乘法原理用拟合的方法自诊断单点受我的位置。
After a data library about standard samples is established on the basis of the experiment, the locution of the single-point load on the structure is self-diagnosed by means of the least square method.
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