Fuzzy Forecast of Nonlinear Time-series Data

The field of forecasting is considered as an application of time-series analysis even if the data is linear or nonlinear. To obtain the forecasted values from observed data exerts a big influence on the decision-making support system or the control of machine etc. The nonlinear data appear as the random enumerated data. However we sometimes find that the pattern of past appearance repeats itself when we try to observe these data locally. From this point of view, we propose a way of forecasting nonlinear data from the pattern of past appearance using fuzzy theory. The advantages of the method are that we can forecast the next data by small numbers of previous data, and react to some differences, considering the ambiguous mature of the given data.