提出了采用遗忘因子的自回归（AR）模型的功角预测方法。
The rotor angle predicting method adopting the forgetting index of auto regression (AR) model arithmetic is presented.
本文提出一种基于神经网络的多维自回归模型(AR,NLAR)参数估计方法。
A method of parameter estimation for multi-dimension autoregressive models (ar, NLAR) via neural network is given in this paper.
方法分别建立人口布氏菌病新发病例和发病率的自回归模型。
Methods The autoregressive models of population, new cases and incidence rate for human brucellosis dynamics were set up.
水文方法是利用水文序列资料建立自回归模型和多元递推模型。
The hydrological method is using the hydrological series data to establish the autoregressive and multivariate recurrence models.
结果获得三维自回归趋势面模型及其建模方法。
Results the tri dimensional auto regression trend surface model and the method to build this model were obtained.
基于多项式样条全局光滑方法，建立函数系数线性自回归模型中系数函数的样条估计。
A global smoothing method based on polynomial splines is used to estimate the coefficient functions in functional-coefficient linear autoregressive models.
利用微硅陀螺测量的数据，运用过程辨识理论和时间序列分析方法，建立了陀螺静态漂移的自回归（AR）模型，进而得到连续微分方程。
Based on measured data of micro silicon gyro and time-series theory, the AR model of gyro static drift is established, then the continuous-time differential equation is got.
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。
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.
自回归(AR)参数模型是传统的肌电信号时域分析方法。
Parametric Autoregressive (ar) model is the traditional time-domain EMG signal analyzing method.
本文提出设计可控自回归滑动平均过程(CARMA)的离散时间模型参考自适应控制新方法。
A new method is suggested in this paper for design discrete-time Model Reference Adoptive control (MRAc) for controlled Auto-regressive Moving Average (CARMA) processes.
该文针对风速随机变化的特性，在风速统计特性研究的基础上，用自回归滑动平均(ARMA)方法建立了具有一定功率谱密度特性的风速模型。
This paper deals with stochastic characteristic of the wind speed, and gives an auto-regressive moving-average (ARMA) model for wind speed subjected to particular power spectral density.
分析了传统时间序列分析法建立ARMA模型的不足，提出了一种利用模型阶数判断准则和长自回归法建模的新方法。
The disadvantage of establishing ARMA model with traditional time series analysis is analyzed; a new model building method based on judgment rules and long autoregression is put forward.
最后根据该方法组成了一个自回归时间序列模型库，用于转子故障的模型诊断中。
Then, an observer bank of autoregressive time series models based on multi-component neural-network architecture is used for model diagnosis of rotor fault vibration signals.
本文在基于向量自回归类模型的方差分解这一分析框架下将前人实证研究的方法和结论统一在一个新的分析框架内，并完整而细腻地描述了二者的相互关系。
In this paper we use the variance decomposition of the vector error correction model(VECM) to perfectly and detailedly show the relationship between the housing price and the land price.
文中给出RTVAR模型和GRTVAR模型参数的估计方法，并建立广义回归—时变自回归预测公式。
The parameter estimation of RTVAR and GRTVAR models and the GRTVAR prediction formulas are also established.
该文在分析了时间序列模型的自回归系数对结构单元刚度灵敏度的基础上，提出了一种采用随机载荷作用下结构的时域响应数据进行损伤识别的新方法。
A new method is developed for identifying structural damages at the element level by using time-domain response data at a few points caused by random loadings.
本文提出一种新的多项式信号加自回归AR噪声的组合模型统计处理方法。
A new AR mixed model statistics method dealing with electric measure data of aircraft is presented.
本文概述了时序分析的非线性模型类，详细叙述了门槛自回归模型的建模思想和方法。
In this paper a variety of time series nonlinear models are introduced and the idea and modeling method of the threshold autoregression are discussed in detail.
方法采用自回归移动平均模型对出院人次进行模型拟合。
Methods Using the Autoregressive Integrated Moving Average Model to fit the change of numbers of discharged patients.
提出了基于自回归(AR)模型对时间序列统一建模的新观点和方法，可大大减少计算量，并在微机上编程实现。
This article issues a new viewpoint and method in modeling for time series based on ar model. The method is able to give less calculating and to be programmed on computer.
同时，基于已有的AR（1）模型，提出了一种改进型AR（1）自回归模型，该模型能够利用历次服务器响应时间构成的时间序列，采用动态预测的方法来预测服务器响应时间。
Then, an improved AR(1) model is proposed. Through this new model, the response time of a DNS server can be dynamic predicted using previous response time series.
基于自回归滑动平均模型（ARMA），利用时间序列建模，提出了利用组合模型对网络流量进行预测的方法。
From the discrete solution of the equation of vibration of engineering structure, the equalility of the neural network based time domain identification and the ARMA model was verified.
基于自回归滑动平均模型（ARMA），利用时间序列建模，提出了利用组合模型对网络流量进行预测的方法。
From the discrete solution of the equation of vibration of engineering structure, the equalility of the neural network based time domain identification and the ARMA model was verified.
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