A New Hesitant Fuzzy-Based Forecasting Method Integrated with Clustering and Modified Smoothing Approach
- 31 March 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in International Journal of Fuzzy Systems
- Vol. 22 (4), 1104-1117
- https://doi.org/10.1007/s40815-020-00829-6
Abstract
No abstract availableKeywords
This publication has 45 references indexed in Scilit:
- Effective intervals determined by information granules to improve forecasting in fuzzy time seriesExpert Systems with Applications, 2013
- A generalized method for forecasting based on fuzzy time seriesExpert Systems with Applications, 2011
- Finding an optimal interval length in high order fuzzy time seriesExpert Systems with Applications, 2010
- Hesitant fuzzy setsInternational Journal of Intelligent Systems, 2010
- FORECASTING FUZZY TIME SERIES ON A HEURISTIC HIGH-ORDER MODELCybernetics and Systems, 2005
- Recursive information granulation: aggregation and interpretation issuesIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2003
- Abstraction and specialization of information granulesIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2001
- Temperature prediction using fuzzy time seriesIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2000
- Exponential smoothing: The state of the artJournal of Forecasting, 1985
- Exponential Smoothing with an Adaptive Response RateJournal of the Operational Research Society, 1967