A Novel Hybrid SBM Clustering Method Based on Fuzzy Time Series

With the development of machine learning algorithm and fuzzy theory, clustering based on time series has received more attention. Based theory considering correlation data attributes, it proposes a novel multivariate method Slacks Measure (MFTS-SBM). Compared with traditional that ability to deal fuzziness uncertainty, proposed hybrid SBM employs input output items considers results influencing factors nonparametric frontier. Thus, is important for decision making because makers are interested in understanding changes required combine variables order classify them into desired clusters. The simulation experiment different samples given explain use effectiveness method. Therefore, strong theoretical significance practical value.