| Popis: |
The present invention relates, in general, to a nonlinear time series prediction method using weighted average defuzzification based on a Neural Network with Weighted Fuzzy Membership functions (NEWFM), and more particularly, to a nonlinear time series prediction method using weighted average defuzzification based on a NEWFM, which measures the classification strengths of respective classes, classified according to NEWFM, determines the classification strengths which indicate membership degrees for respective classes, and predicts a nonlinear time series through the weighted average defuzzification of the classification strengths, so that the nonlinear time series can be applied to the determination and forecasting of an economic phase using a Composite index (CI), thus enabling the nonlinear time series to be used for determining the direction of the economic phase as well as the classification of the economic phase. |
