Abstract:

As for the fluctuating sequences characterized by saturated condition or single-peak, whose development and variation are subject to multi-faceted factors, the coupling prediction model combining the self-memory principle and the optimized GM(1,1)power model has been constructed based on the grey GM(1,1)power model in order to improve prediction accuracy. The traditional grey model’s weakness as being sensitive to the initial value can been overcomed by the self-memory principle of dynamic system. The results indicate that the newly-established model can take full advantage of the systematic multi-time historical data. It extends the grey model’s application span, which possesses higher accuracy of simulation and forecast than the traditional optimized GM(1,1)power model.Finally, the superiority and effectiveness of this proposed model have been proved by the case of Chinese senior high school students’ enrolment rate into higher education institutions.