Fuzzy time series forecasting model based on second order fuzzy logical relationship and similarity measure / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli

Various fuzzy time series (FTS) forecasting methods have been proposed to cater for data in linguistic values. In this paper, an improved FTS forecasting method based on second order fuzzy logical relationship is proposed and it is used to forecast the enrollment of students in the University of Ala...

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Bibliographic Details
Main Authors: Nik Badrul Alam, Nik Muhammad Farhan Hakim (Author), Ramli, Nazirah (Author)
Format: Article
Language:English
Published: Universiti Teknologi MARA, Perak, 2019-12.
Subjects:
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100 1 0 |a Nik Badrul Alam, Nik Muhammad Farhan Hakim  |e author 
700 1 0 |a Ramli, Nazirah  |e author 
245 0 0 |a Fuzzy time series forecasting model based on second order fuzzy logical relationship and similarity measure / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli 
260 |b Universiti Teknologi MARA, Perak,   |c 2019-12. 
856 |z Get fulltext  |u https://ir.uitm.edu.my/id/eprint/39324/1/39324.pdf 
856 |z View Fulltext in UiTM IR  |u https://ir.uitm.edu.my/id/eprint/39324/ 
520 |a Various fuzzy time series (FTS) forecasting methods have been proposed to cater for data in linguistic values. In this paper, an improved FTS forecasting method based on second order fuzzy logical relationship is proposed and it is used to forecast the enrollment of students in the University of Alabama. The performance of the forecasted results is compared to the actual data by using seven different similarity measures. The hybrid similarity measure based on geometric distance, centre of gravity, area, perimeter and height gives the best performance. 
546 |a en 
650 0 4 |a Data processing 
650 0 4 |a Fuzzy logic 
655 7 |a Article