Application of fuzzy time series analysis to change periods detection

Unlike conventional change points detection which seeks to find a decision boundary between classes for certain structural changed time series, the purpose of this research is to investigate a new approach about fuzzy change periods identification. Based on the concept of the fuzzy theory, we propose a procedure for the /spl alpha/-level of fuzzy change period detection and prove some useful properties for a fuzzy time series. We use some numerical examples to demonstrate how these procedures can be applied. Finally, experimental results show that the proposed detection approach for structure change of fuzzy time series is available and practical in identifying the /spl alpha/-level of fuzzy change period.