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1·Experimental study on ship motion prediction using auto regressive model was carried out.

利用自回归模型对船舶运动进行了预报试验研究。

2·Auto regressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with an LMS algorithm.

自适应(AR)模型是数字信号处理中广为应用的一种模型，它的系数可以通过LMS算法求解。

3·The trend part of the data can be fitted with BP (back propagation) neural network and the random part is processed by a normal ARMA (auto regressive moving average) model.

采用BP网络对不平稳时间序列进行数据拟合，处理趋势部分，利用ARMA模型处理随机部分。

4·In this paper, Auto Regressive model of metal content for specially monitored metals in lubricating oil monitoring system of aeroengine is built by the method of Time Series Analysis.

利用神经网络方法对某型航空发动机滑油监控系统中需重点监控的金属元素含量建立了网络，并根据该模型对其含量变化趋势进行了预测分析。

5·The reconstruction of vehicle random vibration signal under different vehicle speed and road conditions is realized in laboratory, based on an auto regressive moving average (ARMA) time series model.

基于自回归滑动平均模型(ARMA)的方法，实现了不同车速和路面条件下的随机振动信号的实验室再现。

6·To solve the problem of modeling temperature control in the fermentation process, a neural network nonlinear auto regressive moving average(NN-NARMA) modeling method for nonlinear system is proposed.

针对生物发酵过程中温度控制难以建模的问题，基于非线性自回归滑动平均（NARMA）模型，设计了神经网络自回归滑动平均（NN-NARMA）模型。

7·This paper makes a positive analysis of the relation of revenue increase and economic growth in Guangxi province applying regression model, auto-regressive and dynamic distributed lag models.

本文运用回归模型、自回归分布滞后模型和动态分布滞后模型对广西税收增长与经济增长的关系进行了实证分析。

8·A novel online fault detection algorithm based on adaptive auto-regressive (AAR) model is proposed focusing on the anomaly detection of network traffic.

通过研究网络流量异常检测，提出一种新的基于自适应自回归(aar)模型的在线故障检测算法。

9·Based on multi variable auto-regressive model, a long-run equilibrium model is correspondingly constructed which lies a foundation for further economic analysis.

基于多变量自回归模型，我们构建了相应的长期均衡关系模型，从而为进一步经济分析奠定了基础。

10·An algorithm of feature extraction and damage alarming based on auto-regressive moving-average (ARMA) time series analysis is presented.

本文基于时间序列分析ARMA模型探讨了结构损伤特征提取和损伤预警的实现方法。