Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models
Muhammad Bilal, Masad A. Alrasheedi, Muhammad Aamir, Saleem Abdullah, Siti Mariam Norrulashikin, Reza Rezaiy · 2024
Read Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models by Muhammad Bilal, Masad A. Alrasheedi, Muhammad Aamir, Saleem Abdullah, Siti Mariam Norrulashikin, Reza Rezaiy (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11611899.txt.
Description
Muhammad Bilal and five co-authors forecast in 2024 rice price and production in Malaysia with new multivariate fuzzy time series models. Rice feeds much of the world, and Malaysia has grown it as its top food crop since the 1960s. Sharper forecasts aid farm and trade planning.
Fuzzy vector models, in triangular and trapezoidal forms, face off against a classic vector model. Data come from the national agricultural research institute. Model choice rests on forecast error and relative efficiency scores. The trapezoidal fuzzy model posts the best accuracy and the strongest future forecasts. The authors argue that fuzzy handling of vague yearly data beats crisp models for crop outlooks in data-scarce settings.
Catalog record
| CREATOR | Muhammad Bilal, Masad A. Alrasheedi, Muhammad Aamir, Saleem Abdullah, Siti Mariam Norrulashikin, Reza Rezaiy |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 103 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |