The purpose of this paper is to realize scientific reasoning and prediction in economic catastrophe, which occurs in the short‐term and leads to invalidation of most classical prediction models through lacking basic sample data.
Based on functional theory, grey number algebra theory, Bayesian network theory and interval grey number theory, the authors established GFAM (1,1), which is grey function analysis model (1,1), to excavate and utilize the existing data sufficiently.
This paper proved least squares parameters theorem and prediction theorem and the process of GFAM (1,1). A case was established and demonstrated the utility and good prediction of this model.
This paper established GFAM (1,1), which overcomes the hysteretic defect of classical prediction model and provides a preferable solution in system prediction in economic catastrophe.
