Modeling of nonstationary time-series data. Part I. Data with regular periodic trends

被引：2

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)00034-X

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 is Part-I of a two-part paper in which composite modeling approach to nonstationary time series forecasting is proposed. Time-series data with regular periodic trends are considered in this paper and data with dynamic trends are treated in the second part of the paper. The major data comprising components are generalized by deterministic models identified through three-step sequential fitting procedure using non-linear regression technique. The proposed modeling approach has been applied to two data sets obtained from two different fields and both containing regular periodic trends. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：57 / 62

页数：6