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

DOI10.1016/J.IJAR.2017.01.006zbMath1407.62325OpenAlexW2571945220MaRDI QIDQ518618

Muhammad Hisyam Lee, Tayyebeh Eslami, Cidiney José da Silva, Frederico Gadelha Guimarães, Hossein Javedani Sadaei

Publication date: 29 March 2017

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2017.01.006

zbMATH Keywords

fuzzy time seriesparticle swarm optimizationSARFIMAshort term load forecasting (STLF)

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and fuzziness (62M86)

Related Items (6)

Fuzzy clustering of time series with time-varying memory ⋮ Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review ⋮ A non-parametric model for fuzzy forecasting time series data ⋮ Designing fuzzy time series forecasting models: a survey ⋮ Statistical inference for time series with non-precise data ⋮ Forecasting based on high-order fuzzy-fluctuation trends and particle swarm optimization machine learning

Uses Software

• forecast
• TDSL
• Forecast
• TSDL

Cites Work

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• FORECASTING ENROLLMENTS BASED ON HIGH-ORDER FUZZY TIME SERIES
• Improving TAIEX forecasting using fuzzy time series with Box–Cox power transformation
• Parallel global optimization with the particle swarm algorithm
• Effective lengths of intervals to improve forecasting in fuzzy time series
• Stock market forecasting by using a hybrid model of exponential fuzzy time series

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