Short-term load forecasting method based on fuzzy time series, seasonality and long memory process

• Main Authors: Sadaei, Hossein Javedani, Guimaraes, Frederico Gadelha, Cidiney Jose, Da Silva, Lee, Muhammad Hisyam @ Wee Yew, Tayyebe, Eslami
• Format: Article
• Published: Elsevier Science BV 2017
• Subjects: Q Science
• Online Access: http://eprints.utm.my/id/eprint/66169/; http://dx.doi.org/10.1016/j.ijar.2017.01.006
• Institution: Universiti Teknologi Malaysia

Seasonal Auto Regressive Fractionally Integrated Moving Average (SARFIMA) is a well-known model for forecasting of seasonal time series that follow a long memory process. However, to better boost the accuracy of forecasts inside such data for nonlinear problem, in this study, a combination of Fuzzy...