Sci-Fts: Using Soft Clustering on Intrinsic Mode Functions to Model Fuzzy Time Series

This manuscript introduces a new software, sci-FTS, which models time series by combining Signal Processing tools and Fuzzy Set Theory. Firstly, time series are decomposed into Intrinsic Mode Functions (IMFs), emphasizing instantaneous frequencies and amplitudes. Secondly, sci-FTS combines IMFs to extract deterministic influences, removing noises. Next, sci-FTS executes an algorithm that finds an adequate space partitioning to produce the fuzzy sets. Finally, Fuzzy Time Series steps are considered to predict observations. Our contributions are twofold: sci-FTS finds out similar patterns in observations to better model the universe of discourse; ii) models produced by sci-FTS overcome studies from the literature.