In this paper, autoregressive moving average model (ARMA) is used to forecast the power load.
本文采用自回归滑动平均模型(ARMA)对电力负荷进行了预测。
Methods Using the Autoregressive Integrated Moving Average Model to fit the change of numbers of discharged patients.
方法采用自回归移动平均模型对出院人次进行模型拟合。
We obtain some results as follows:In chapter 2, a new mixture autoregressive moving average model is proposed for modeling nonlinear time series.
提出了一类新的用于非线性时间序列建模的混合自回归滑动平均模型。
This paper uses the recursion algorithm of the least-square method to identify an autoregression model and an autoregression moving average model.
本文用最小二乘递推算法辨识自回归模型和自回归动平均模型，编制了电力系统短期在线负荷予报程序。
A mixed autoregressive moving average (MARMA) model is proposed for modeling nonlinear time series.
提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA)。
The theory of linear regression and the theory of moving average are applied to analyse single data in time series, the model of a linear moving self regression forecast are given out.
应用线性回归分析和移动平均理论，对按时间次序排列的单一数据序列，给出了一种线性移动自回归预测模型，并对原始数据受不确定因素影响而产生的随机振荡，给出了合理的控制区间和运行通道。
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。
The parameter estimation problem to the invertible vector moving average (ma) model essentially is a matrix spectral factorization problem.
可逆的向量滑动平均(MA)模型参数估计问题本质上是一个矩阵谱分解问题。
Methods The trend values were calculated and the monthly indexes were adjusted with moving average method of season prediction method, and then the model was applied.
方法用季节预测法中的移动平均比率法计算趋势值与调整月指数 ，最后应用模型。
Then we use adaptive exponentially weighted moving average (AEWMA) control charts to control the process which satisfies the two-component model.
接下来就是进行过程监控方法的研究。本文主要对生产过程利用可适应性指数加权滑动平均(aewma)法进行质量控制。
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.
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。
Then, we make prediction with moving exponential average model after the analysis of the travel time series. Finally, we present reasonable justification.
通过分析行程时间时间序列的时变特性，利用指数平滑模型进行预测，最后提出合理的修正方法。
The optimal moving average filter for the linear stochastic controlled plant is developed from the viewpoint of the internal model of the deterministic disturbance.
从确定性干扰的内模观点导出了适用于线性随机受控对象的最优滑动滤波器。
In Chapter 2, two moving average risk models are introduced to model the surplus process, and the probabilities of ruin are examined in models with a constant interest force.
在第二章，我们分别用二个滑动平均模型去模拟盈余过程。在常值利率的作用下我们来研究该类模型的破产概率。
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.
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。
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。
Through the data obtained by fieldwork, the paper forecasts the short-term traffic by three methods: moving-average method, index-smoothing method, AR model method.
本文通过实地调查获取的交通流量数据，分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。
Through the data obtained by fieldwork, the paper forecasts the short-term traffic by three methods: moving-average method, index-smoothing method, AR model method.
本文通过实地调查获取的交通流量数据，分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。
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