This study proposes the model for interpolating time series to use them  to forecast effectively for future. This model is established based on the improved fuzzy clustering analysis problem, which is implemented by the Matlab procedure. The proposed model is illustrated by a data set and tested for many other datasets, especially for 3003 series in  M3-Competition data. Comparing  to the exist...

Periodic time series analysis refers to the modelling approach where important time series properties depend on the period of the year. The standard approach to time series modelling is to treat a time series as a stochastic process with seasonal fluctuations. In a periodic analysis seasonal variations are modelled using separate yearly time series for each season, which do not possess seasonal...

The method of analyzing data known as Discrete Mathematical Analysis (DMA) incorporates fuzzy mathematics and logic. This paper focuses on applying DMA to study the morphology time series by utilizing language mathematics. morphological characteristics series, such background, slopes, vertices, are considered sets within domain its definition. allows for use logic in examining ultimately leadin...