Prediction of Social Ownership of Typical Household Appliances Based on Improved Grey Models

Abstract

With the advent of complicated system of electronic and electrical household appliances, the prediction of the social ownership based on a single time series does not conform to its nonlinear growth law. In the present study, the main factors affecting the social ownership of household electronics and electrical appliances are initially investigated based on the grey relational model. Then the main influencing factors are considered to construct a multiple grey prediction model. Moreover, the model is optimized by various intelligent algorithms to improve prediction accuracy. Finally, the model accuracy is evaluated through the social ownership data of four typical household appliances in Jiangsu province. The optimized model is applied to predict the social ownership of household appliances in Jiangsu province in the period 2020 to 2022. The results of this article may provide a basis for promoting the resource utilization of e-wastes and assisting managers to improve electronic waste recycling.