ARMA model has been widely used in stochastic hydrologic field.
ARMA模型在随机水文学及其他领域中有广泛的应用。
After thorough analysis these tests data, design a corresponding ARMA model.
深入分析寿命试验数据，并对其建立arma模型。
Several criteria such as AIC and SIC are usually used in ARMA model selection.
AIC与SIC等准则函数方法是arma模型选择过程中经常使用的方法。
In this paper a linear method for parameter estimation of ARMA model is proposed.
本文提出估计ARMA模型参数的一种线性方法。
It is shown that an ARMA model of minimum order exists for a given target spectrum.
论文表明，对给定的目标谱，存在一最低阶的ARMA模型。
In this paper, the mathematic models for sea waves are expressed as the ARMA model.
本文研究了用arma模型描述海浪运动的数学模型。
ARMA model of nonlinear structural vibration and control systems were studied in this paper.
本文研究了结构非线性振动及其控制系统的ARMA模型的建立问题。
With analysis of meteorological temperature data, ARMA model is produced to predict and control the system.
并对气象温度数据进行了ARMA建模，对系统进行预测报警。
Compared with one-order linear model, ARMA model and fuzzy reasoning model, this model has better writing effect.
与一阶线性模型、ARMA模型和模糊推理模型进行比较，结果表明该模型的书写效果较好。
Power function, periodical function, and ARMA model are established according to the characteristics of sub-series.
然后根据各子序列的特性分别建立幂函数、周期函数或ARMA模型并进行预测。
To the ununiqueness of multiple ARMA model, in the paper we give a restriction that makes multiple ARMA model be unique.
本文针对多元ARMA模型形式的不唯一性，给出了一个限制条件，使得多元ARMA模型的形式具有了唯一性。
At present, the time series analysis method often USES AR or ARMA model, this method is very complicated and difficult to apply.
目前时间分析方法多采用AR或ARMA模型，但由于实际问题错综复杂，导致模型求解困难，实际中难以应用。
The recursive neural network based nonlinear approaching ARMA model is adopted for short-term power load prediction in this paper.
本文用递归神经网络逼近非线性ARMA模型预测电力短期负荷。
However, when the order of ARMA model is very high, to compare every candidate model's criterion value is computationally infeasible.
但是，当模型的阶数很高时，无法计算并比较每一个备选模型的准则函数值。
This paper introduces the feasibility of inner recursion networks using in non-linear ARMA model approaching and time series forecasting.
该文介绍了内回归神经网络逼近非线性ARMA模型、用于时间序列预测的可行性。
We use ARMA model to describe the seismic wavelet, and use genetic algorithms to estimate the ar parameters and the ma parameters iteratively.
该方法用ARMA模型描述地震子波，用遗传算法交替迭代地估计AR和MA参数。
ARMA model is one of the most common models in the modern time series analysis which is widely used in scientific researches and engineering systems.
ARMA模型是现代时间序列分析中最为常用的模型之一，在科学研究和工程系统中具有广泛的运用。
In this paper, the method of weighted least square estimate is proposed to construct ARMA model, which can be applied in power system load forecasting.
采用加权最小二乘法参数估计方法，得到应用于电力系统日负荷预测和月负荷预测的ARMA模型。
The ARMA model was used to describe the prior distribution of observed discharge and the ar model was adopted to simulate the likelihood function of forecasting error.
该模型采用ARMA模型描述实测流量的先验分布，采用AR模型模拟预报残差的似然函数，并假定先验分布和似然函数均服从正态分布。
Combined with certain type time series recount multiplicity model and random type ARMA model, establish the time series model of the death rate in Chongqing urban area.
应用确定型的时间序列分解法乘法模型与随机型的arma模型相结合，建立重庆市主城区人口死亡率的时间序列模型。
It is shown that the second order structure is similar to a linear ARMA model with uncorrelated errors. In the end, the best linear predictors are given for USDBL models.
证明了该模型的二阶特性与一个线性平稳arma模型相似，最后给出了该模型的最优化线性预报方法。
Then algorithm analysis of network traffic model, a brief introduction of the Poisson model, Markov model, ar, MA, ARMA model, focused on analyzing ARIMA model algorithm.
接着对网络流量模型算法分析，简单介绍了泊松模型，马尔科夫模型，AR,MA,ARMA模型，重点分析了ARIMA模型算法。
This paper bases on lattice iterate identification method for ARMA model, pushes out its recursive algorithm, puts forward a determination order method for this algorithm.
本文针对ARMA模型的格型迭代法，推出了它的递推算法，并针对本算法提出了相应的判价方法。
Moreover, SVM-based forecasting model performs faster than ARMA model to forecast the communication traffic. Generally speaking, the overall performance of SVM model is optimal.
而且SVM的预测速度明显比arma模型快，综合各方面考虑，SVM预测模型的整体性能最优。
The results of numeric simulation and real seismic data processing showed that the ARMA model was characterized by parameter-economic and high efficiency in comparison with MA model;
数值模拟结果和实际地震数据处理结果表明：自回归滑动平均（ARMA）模型比滑动平均（MA）模型具有参数节省、模型更为高效的特点；
Through study, the noise of time series have decreased a lot compared to primary time series, and we can concluded that ARMA model is a good method for research GPS height time series.
通过研究表明利用ARMA模型有利于降低GPS高程时间序列噪声，可用于GPS高程时间序列的分析和研究。
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.
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。
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