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。
The traditional methods are the sum of autoregressive moving average model, nonparametric regression models and so on. 传统的预测方法有求和自回归移动平均(ARMA)模型,非参数回归模型等。
This paper focusses on analysing properties of Autoregressive Moving Average(ARMA) ( ARMA ) model in frequency domain. 本文分析了自回归滑动平均(ARMA)模型的频域特性;
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)。
To presents a supply chain model based on autoregressive moving average ( ARMA ) times-series. 在基于ARMA时间序列的需求和目标库存最大策略的假定条件下,建立了供应链系统模型。