A novel Hausdorff fractional grey Bernoulli model and its Application in forecasting electronic waste

Abstract

This study presents the Hausdorff fractional NGBM (r,1), a novel prediction approach developed based on the original nonlinear grey Bernoulli model; NGBM(1,1). The approach integrates the Hausdorff fractional accumulation operator and provides greater degrees of freedom. The recurrence relation of the binomial in the discrete solution also provides simpler computation due to the elimination of the Gamma function calculation. The Jaya Algorithm is introduced to optimize the parameters of the new model to improve its adaptability. The proposed model and its findings are delineated with the help of two case studies utilizing e-waste data from United Kingdom and State of Connecticut. The proposed model is benchmarked with several existing forecasting models and the calculated Mean Absolute Percentage (MAPE) is compared. The findings demonstrate that the proposed model exhibits superior fitting and predictive accuracy in comparison to the existing models. It produced lower MAPE than its counterparts.