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 existing models, the proposed model always gives the best result. We also apply the proposed model in forecasting the salt peak for a coastal province of Vietnam. Examples and applications show the potential of the studied problem.
Tai, V. V., & Nghiep, L. D. (2020). Interpolating time series based on fuzzy cluster analysis problem. Iranian Journal of Fuzzy Systems, 17(3), 151-161. doi: 10.22111/ijfs.2020.5355
MLA
V. V. Tai; L. D. Nghiep. "Interpolating time series based on fuzzy cluster analysis problem". Iranian Journal of Fuzzy Systems, 17, 3, 2020, 151-161. doi: 10.22111/ijfs.2020.5355
HARVARD
Tai, V. V., Nghiep, L. D. (2020). 'Interpolating time series based on fuzzy cluster analysis problem', Iranian Journal of Fuzzy Systems, 17(3), pp. 151-161. doi: 10.22111/ijfs.2020.5355
VANCOUVER
Tai, V. V., Nghiep, L. D. Interpolating time series based on fuzzy cluster analysis problem. Iranian Journal of Fuzzy Systems, 2020; 17(3): 151-161. doi: 10.22111/ijfs.2020.5355