Forecasting international migrants using grey model with heat label

Abstract

Migration is an important social phenomenon in the development of human society. Driven by economy, population, geography, policy, and other factors, accurate prediction of migration has always been very difficult. The grey model has the advantages of small sample size, easy calculation, no regularity in sample size, and good prediction precision, so it is very suitable for the prediction of international migration. Based on the correlation and cumulative effect of data sequence, this paper optimizes the initial value conditions of the grey model, and proposes the grey model of heat label. The proposed model is applied to the prediction of international migration from 1970 to 2020, and compared with the traditional grey model and other models, computation results show the model is practical and effective, and has positive theoretical and practical significance for international migration prediction.