To read about Beloit’s ongoing coronavirus response, visit our COVID-19 information site.

Nonlinear Grey Bernoulli Model


Presentation author(s)

Hoàng Thái Nam ’23, Ho Chi Minh City, Vietnam

Major: Computer Science

Abstract

The Nonlinear Grey Bernoulli Model NGBM(1,1) is a recently developed grey model that has various applications in different fields, mainly due to its accuracy in handling small time-series datasets with non-linear variations. In this paper, to fully improve the accuracy of this model, a novel model is proposed, namely Rolling Optimized Nonlinear Grey Bernoulli Model RONGBM(1,1). This model combines the rolling mechanism with the simultaneous optimization of all model parameters (exponential, background value and initial condition). The accuracy of this new model is significantly confirmed by forecasting Vietnam’s GDP from 2013 to 2018 before it is applied to predict the total COVID-19 infected cases globally by day.

Sponsor

Mehmet Dik

This site uses cookies to improve your experience. Read our Web Privacy Policy for more information.

Got it! ×