Affiliation of Author(s):经济与管理学院
Journal:Kongzhi yu Juece Control Decis
Abstract:Aiming at the problem that traditional grey multi-variable discrete models don't consider the time-delay dynamic characteristics and the utilization of previous data of the driving variables, a new grey multi-variable discrete model, abbreviated as DDGMD(1,N), is constructed. And a model parameter calculation method is discussed by introducing adjustment coefficient Tiand effect coefficient λiof the driving information control. Then, the adjustment coefficient is identified by using the method of grey extended dimension identification, which clarifies the driving variables and their time-delay parameters. The effect coefficient is determined, which reflectes the influence of the previous data of driving variables to the system behavioral sequence, by using the particle swarm optimization algorithm. Finally, a real application about the forecast of the energy consumption in Jiangsu Province is used to demonstrate the feasibility and practicability of the DDGMD(1,N) model. The validity of the model is proved to be suitable for the prediction of small sample data with time-delay characteristics. © 2017, Editorial Office of Control and Decision. All right reserved.
ISSN No.:1001-0920
Translation or Not:no
Date of Publication:2017-09-01
Co-author:魏龙
Correspondence Author:dyg
Date of Publication:2017-09-01