An improved grey multivariable time-delay prediction model with application to the value of high-tech industry. Expert Systems with Applications

Date

2022-10-20

Advisors

Journal Title

Journal ISSN

ISSN

0957-4174

Volume Title

Publisher

Elsevier

Type

Article

Peer reviewed

Yes

Abstract

To analyse the time lag effects between independent variables and dependent variables, we propose a discrete time-delay grey multivariable model . There are three improvements in this new model compared to the existing models. First, the time lag parameters are assigned different values for each independent variable. A linear correction term expands the new model. Second, with the given time lag, the least square method can be used to calculate the parameter vector. The time response function of is generated, which has the advantage of eliminating the jumping errors between discrete and continuous functions over the existing grey forecasting models. Third, all of the feasible combinations of the time lag parameters are compared by using a traversal algorithm to identify the best values with the minimized mean absolute percentage error (MAPE). In three different case studies, the performance of the new model is evaluated and compared to that of a number of mainstream grey models as well as non-grey models. According to the findings, the newly designed model performs significantly better than the compared models.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link

Keywords

grey multivariable model, Forecasting, time delay, linear correction term, high-tech industry

Citation

Zhou, H., Dang, Y., Yang, D., Wang, J. and Yang, Y. (2023) An improved grey multivariable time-delay prediction model with application to the value of high-tech industry. Expert Systems with Applications, 213, Part B, 119061

Rights

Research Institute

Institute of Artificial Intelligence (IAI)