Modeling of nonstationary time-series data. Part II. Dynamic periodic trends

被引：22

作者：

Barakat, EH ^{[1
]}

机构：

[1] SCECO Cent Reg, Tech Studies Dept, Riyadh 11411, Saudi Arabia

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2001年 / 23卷 / 01期

关键词：

time series; forecasting; dynamic trends; regression;

D O I：

10.1016/S0142-0615(00)00035-1

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents deterministic models for simulating nonstationary time-series data with dynamic periodic trends. These models have been applied to monthly energy data recorded in the lunar calendar. Simulation results have shown good accuracy when compared with results obtained from established modeling techniques. The models developed in this paper are useful not only to electric utilities using the lunar calendar but also to those utilities faced with the modeling of data whose actual length of seasonality is not known precisely. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：63 / 68

页数：6