Time series, Fuzzy transform, statistical

The primary objective of this research is to evaluate and contrast the effectiveness of several techniques for finding structural breaks in time series. We will consider several methods. Chow test (1960), the Chow test is a method for identifying structural breaks in time series by comparing different regression coefficients and intercept terms. This method is founded on the idea that different intercept terms can be used to discover these breaks. It compares the null hypothesis of ``no structural break" with the alternative hypothesis of ``a structural break exists". Pettitt's method developed in 1979 is typically utilized when trying to identify a single change point in a time series. It tests the null hypothesis: the variables follow one or more distributions that have the same location parameter (no changepoint). In the Buishand test (1982), which is based on the assumption that the data follow a normal distribution, the data are dispersed arbitrarily and independently in accordance with the null hypothesis (no break). This test is particularly sensitive to disruptions in the middle of the time series.