The electric power load forecasting is critical for stable electric power system supply. In this paper, a seasonal ARIMA model was used to effectively forecast power load data characterized using periodicity. A numerical example reveals that the seasonal ARIMA model effectively forecast periodic power load.

This study compares X-12-ARIMA and MING, two new seasonal adjustment methods designed to handle outliers and structural changes in a time series. X-12-ARIMA is a successor to the X-ll-ARIMA seasonal adjustment method, and is being developed at the U.S. Bureau of the Census (Findley et al. (1988)). MING is a “Mixture based Non-Gaussian” method for sea* sonal adjustment using time series structur...

This paper works on the agricultural drought forecasting in the Guanzhong Plain of China using Autoregressive Integrated Moving Average (ARIMA) models based on the time series of drought monitoring results of Vegetation Temperature Condition Index (VTCI). About 90 VTCI images derived from Advanced Very High Resolution Radiometer (AVHRR) data were selected to develop the ARIMA models from the er...

Kalman filters and ARIMA models provide optimum control and evaluation techniques (in a minimum squared error sense) for clocks and precision oscillators. Typically, before the models can be used, an analyeie of data provides estimates of the model parameters (e.g., the phi's and theta's for an ARIMA model). These model parameters are often evaluated in a batch mode on a computer after a large ...

OBJECTIVES To investigate the impact of Australia's plain tobacco packaging policy on two stated purposes of the legislation--increasing the impact of health warnings and decreasing the promotional appeal of packaging--among adult smokers. DESIGN Serial cross-sectional study with weekly telephone surveys (April 2006-May 2013). Interrupted time-series analyses using ARIMA modelling and linear ...

This article reviews the practical aspects of the use of ARIMA (autoregressive, integrated, moving average) modelling of time series as applied to the surveillance of reportable infectious diseases, with special reference to the widely available SSS1 package, produced by the Centers for Disease Control and Prevention. The main steps required by ARIMA modelling are the selection of the time seri...

As to the established gray model based on the linear time-variant and individual prediction model of ARIMA, this article constructs the combined forecasting model based on the gray model and the time series model by means of relative error weighing. This prediction indicates that both the gray model and ARIMA model exert efficient function on the Torpedo development cost prediction, and the com...

Traditionally, the autoregressivemoving average (ARMA)model has been one of themost widely used linear models in time series prediction. Recent research activities in forecasting with artificial neural networks (ANNs) suggest that ANNs can be a promising alternative to the traditional ARMA structure. These linear models and ANNs are often compared with mixed conclusions in terms of the superior...

Extended Thermodynamics of dense gases is characterized by two hierarchies of field equations, which allow one to overcome some restrictions on the generality of the previous models. This idea has been introduced by Arima, Taniguchi, Ruggeri and Sugiyama. In the case of a 14-moment model, they have found the closure of the balance equations up to second order with respect to equilibrium. Here, ...