IFS and SODA based computational method for fuzzy time series forecasting
作者：
Highlights：
• A computational method based on IFS is proposed for FTS forecasting.
• Proposed method uses non-parametric clustering technique of SODA to partition UOD.
• Proposed method uses GWO to optimize the weights used in computational algorithm.
• University of Alabama enrolments, share price are forecasted using proposed method.
• Proposed method lowers RMSE and AFER in forecasting enrolments and SBI share.
摘要
•A computational method based on IFS is proposed for FTS forecasting.•Proposed method uses non-parametric clustering technique of SODA to partition UOD.•Proposed method uses GWO to optimize the weights used in computational algorithm.•University of Alabama enrolments, share price are forecasted using proposed method.•Proposed method lowers RMSE and AFER in forecasting enrolments and SBI share.
论文关键词：Intuitionistic fuzzy set,Fuzzy time series,Self-organized direction aware,Computational algorithm,Grey wolf optimization
论文评审过程：Received 18 February 2022, Revised 27 June 2022, Accepted 16 July 2022, Available online 22 July 2022, Version of Record 31 July 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118213
