1) ARIMA seasonal multiple model
ARIMA季节乘积混合模型
1.
Presented in this paper are traffic prediction models based on application layer,which use ARIMA seasonal multiple model(p,d,q)(P,D,Q)s for modeling and forecasting the seasonal time series from China\'s exports of a metro area network link.
因此提出基于应用层的流量预测分析模型,对国内某城域网出口链路上的应用层流量序列采用ARIMA季节乘积混合模型(p,d,q)(P,D,Q)s建模并预测。
2) multiple seasonal ARIMA model
ARIMA季节乘积模型
1.
Objective:To establish a model of multiple seasonal autoregressive integrated moving average(ARIMA) (p,d,q)(P,D,Q) s on month-morbility of Bacillary Dysentery,and to explore the applications of multiple seasonal ARIMA model.
结论:通过ARIMA(0,0,1)(0,1,1)12模型与ARIMA(0,1,1)12模型对细菌性痢疾月发病数预测效果的比较,表明ARIMA季节乘积模型是一种短期预测精度较高的预测模型。
3) multiplicative seasonal Autoregressive Integrated Moving Average
乘积季节ARIMA
1.
Based on the characteristics exhibited in the traffic series,multiplicative seasonal Autoregressive Integrated Moving Average mode(l ARIMA) is employed to make traffic series prediction.
深入研究了某省某移动网络运营商的多年的话务量数据,利用自相关函数对其周期性和趋势性方面的规律进行了探测,并在此基础上提出应用乘积季节ARIMA模型进行建模和预测的方案。
4) multiple seasonal ARIMA
乘积季节性ARIMA
1.
In this paper, the product of the multiple seasonal ARIMA model with the previous comparison of the scheduling method, uses the heating system has been collecting real-time data to forecast the next sampling time values.
本文采用乘积季节性ARIMA模型与以往其他的调度方法进行比较,利用采集得到的供热系统的实时数据来预报下一个采样时刻的预报值,并以此为依据用于供热系统的优化调度,将对供热系统的节能运行和实时控制起到重要作用。
5) seasonal ARIMA model
季节ARIMA模型
1.
Study of electricity sales forecasting for North China Power Grid based on seasonal ARIMA model
基于季节ARIMA模型的华北电网售电量预测研究
2.
In order to improve the accuracy of seasonal highway traffic volume forecasting,a general expression of seasonal ARIMA model with periodicity was presented based on the normal ARIMA model,and then the procedures of modeling and forecasting via seasonal ARIMA model were provided.
与三个常用季节预测模型:分组回归模型、可变季节指数预测模型和季节周期回归模型相比,季节ARIMA模型的预测精度最高。
3.
A seasonal ARIMA model was used to simulate the time series of Lianyungang coastal SST based on the monthly SST from 1996 to 2007,and the optimal model ARIMA(1,0,1)(0,1,0)12 was finally established with its structure determined according to the criteria of residual un-correlation and concision.
基于1996—2007年逐月时间序列数据,采用季节ARIMA模型对连云港近海表层水温时间序列进行模拟,并依据残差不相关和简洁性原则确定模型的结构,建立最优预测模型ARIMA(1,0,1)(0,1,0)12。
6) seasonal ARIMA models
季节ARIMA模型
1.
Since power load has obvious seasonal character,seasonal ARIMA models can be applied to capturing the power hehavior.
将季节ARIMA模型引入电力负荷的建模及预报,为电力资源分配的宏观调控及电网改造提供了一种可靠的方法和途径。
补充资料：[3-(aminosulfonyl)-4-chloro-N-(2.3-dihydro-2-methyl-1H-indol-1-yl)benzamide]
分子式：C16H16ClN3O3S
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条