Purpose This study aims to enhance the traditional multivariate grey Verhulst model by constructing a new-structure model, which is then applied to predict coal consumption in Shandong Province, China. Design/methodology/approach Building upon the traditional multivariate grey Verhulst model, this study incorporates linear and nonlinear correction terms as well as constant terms. Additionally, the traditional whitenization equation is replaced by a difference equation. These modifications address the inherent structural and parameter defects of the original model. Findings The proposed model demonstrates superior performance in simulating and predicting coal consumption compared to other grey Verhulst models. When applied to Shandong Province, the model forecasts that coal consumption will continue to fluctuate within a certain range in the foreseeable future. Originality/value This paper introduces a new model derived from the traditional multivariate Verhulst model, offering an improved structure and enhanced modeling capabilities. The model has been successfully applied to coal consumption forecasting in Shandong Province, contributing not only to more accurate predictions of regional coal consumption but also to the advancement of grey forecasting methodologies.
Zeng et al. (Wed,) studied this question.