| 1. | Autoregressive moving average model
自回归滑动平均模型 |
| 2. | Autoregressive moving average
自回归滑动平均 |
| 3. | Compared to the traditional parameter - fixed autoregressive moving average ( arma ) method , the mep algorithm is adaptive and capable of tracking rtt dynamics rapidly
与传统的参数固定的自回归滑动平均( arma )方法比较， mep算法是自适应的并能够迅速动态地跟踪rtt 。 |
| 4. | Narma ( nonlinear autoregressive moving average ) neutral network current controller of pmsm is proposed and it in company with neutral network speed regulator composes the pmsm vector control system
提出永磁同步电动机的narma神经网络电流控制器，并以神经网络速度控制器和narma电流控制器构成电动机矢量控制系统。 |
| 5. | Immunity mix algorithm based on the continuous differential function is proposed in this paper , and its astringency is proved . from here we get the accurate estimator method of the autoregressive moving average model coefficient
本文首先提出了通用的基于连续可导函数的免疫混合算法，并证明了其收敛性，由此我们得到了自回归滑动均值模型系数的精确估计方法。 |
| 6. | Two - stage algorithms of parameter estimation for the autoregressive moving average ( arma ) models are presented , which are called two - stage recursive least squares algorithm ( 2 - rls ) and recursive least squares - pseudoinverse algorithm ( rls - pi )
本文提出了自回归滑动平均( arma )模型的两段参数估计算法：两段递推最小二乘算法( 2 - rls )和递推最小二乘-伪逆算法( rls - pi ) 。 |
| 7. | In this thesis , autoregressive moving average ( arma ) models are applied to identify the flow regimes of two - phase flow . experiments are carried out on the facilities include gas - solid fluidized bed and gas - liquid two - phase flow pipelines . the results show that the methods are effective
本文基于arma ( autoregressivemovingaverage )模型，对气固流化床和气液两相流系统进行了分析并进一步对其流型进行了辨识，得到了一些有益的结论。 |
| 8. | This system adopts cumulatively autoregressive moving average model [ arima ] of time series method and modified model gm ( 1 , 1 ) of grey system , makes a local load forecasting modeling through the integration of the above two models and also preprocesses the daily load during the sudden change of climate , thus greatly improving the forecast accuracy . the practical operation indicates that the model is reasonable and easy to operate with complete function
本系统在经过反复试算后，在算法上采用了时间序列法的累积式自回归动平均模型( arima )与灰色系统中的gm ( 1 ， 1 )改进模型，并将两种模型组合用于该地区负荷预报建模，另外还对气候急变日负荷进行了预处理，大大提高了预报准确度。 |
| 9. | Based on the classical least squares method ( rls ) in system identification , the several new identification algorithms of parameter estimation for the autoregressive moving average ( arma ) model , are presented . they include univariable and multivariable two - stage recursive least squares - recursive extended least squares ( rls - rels ) and two - stage recursive least squares - pseudo - inverse ( rls - pi ) algorithms
本文在系统辨识经典的最小二乘法( rls )的基础上，提出了自回归滑动平均( arma )模型参数估计的一些新的辨识算法，它包括单变量和多变量两段递推最小二乘?递推增广最小二乘( rls ? rels )算法和两段递推最小二乘?伪逆( rls ? pi )算法等。 |
| 10. | According to the needs of gps / sins integrated navigation algorithm , the error models of gps and sins are studied respectively . the autoregressive ( ar ) models and autoregressive moving average ( arma ) models of gps positioning error are established based on the analysis of the properties of static gps positioning error data . and the neural network method to determine the ar model parameters is given
根据gps / sins组合导航算法的需要，分别对gps和捷联系统的误差模型进行了研究，在对gps静态定位误差数据特性分析的基础上，建立了gps定位误差的自回归( ar )模型和自回归滑动平均和( arma )模型，并用神经网络方法确定了ar模型参数。 |
