A summary of grey forecasting models

Abstract

PurposeThe purpose of this paper is to summarize progress of grey forecasting modelling, explain mechanism of grey forecasting modelling and classify exist grey forecasting models.Design/methodology/approachGeneral modelling process and mechanism of grey forecasting modelling is summarized and classification of grey forecasting models is done according to their differential equation structure. Grey forecasting models with linear structure are divided into continuous single variable grey forecasting models, discrete single variable grey forecasting models, continuous multiple variable grey forecasting models and discrete multiple variable grey forecasting models. The mechanism and traceability of these models are discussed. In addition, grey forecasting models with nonlinear structure, grey forecasting models with grey number sequences and grey forecasting models with multi-input and multi-output variables are further discussed.FindingsIt is clearly to explain differences between grey forecasting models with other forecasting models. Accumulation generation operation is the main difference between grey forecasting models and other models, and it is helpful to mining system developing law with limited data. A great majority of grey forecasting models are linear structure while grey forecasting models with nonlinear structure should be further studied.Practical implicationsMechanism and classification of grey forecasting models are very helpful to combine with suitable real applications.Originality/valueThe main contributions of this paper are to classify models according to models' structure are linear or nonlinear, to analyse relationships and differences of models in same class and to deconstruct mechanism of grey forecasting models.

An unequal new information priority grey forecasting air pollution urban model considering the regional socio-economic development

“…Due to the grey cumulative transformation and differential equation modeling techniques, grey models can complete the system analysis when the data are not less than four samples (Chen et al 2020;Xie and Wang 2017). Among them, grey correlation analysis models and grey prediction models are commonly used in air quality studies.…”

Exploring the mechanism of grey forecasting models: A perspective from dynamic system modelling

“…To describe the competitive relationship between multiple variables, Gatabazi et al [21] constructed a grey continuous Lotka-Volterra model based on Lotka-Volterra differential equation. The latest review [22] has made a systematic and comprehensive exposition for the development of the current grey forecasting model.…”

Grey system theory in engineering: a bibliometrics and visualization analysis

“…After 40 years of development, the research content of the GST has been continuously enriched and expanded. The GST has formed a rich theoretical content based on the grey number, grey relational analysis model, grey clustering evaluation model, grey GM (Grey Model) series model, grey decision model and other models (Xie and Wang, 2017) and has been widely applied in natural science, social science, engineering and other fields, providing a powerful and practical systematic theoretical framework for solving practical problems.…”