An integrated method based on relevance vector machine for short-term load forecasting

DOI10.1016/j.ejor.2020.04.007zbMath1487.91076OpenAlexW3027998989MaRDI QIDQ2023919

Maolin Wang, Jia Ding, Vassilios S. Vassiliadis, Zuowei Ping, Dongfei Fu

Publication date: 3 May 2021

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2020.04.007

zbMATH Keywords

wavelet transformmachine learningshort-term load forecastingfeature selectionrelevance vector machine

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Economic models of real-world systems (e.g., electricity markets, etc.) (91B74)

Cites Work

• Unnamed Item
• Forecasting day-ahead electricity load using a multiple equation time series approach
• Forecasting time series with multiple seasonal patterns
• Electric load forecasting methods: tools for decision making
• Short-run electricity load forecasting with combinations of stationary wavelet transforms
• Structural combination of seasonal exponential smoothing forecasts applied to load forecasting
• 10.1162/15324430152748236
• Short-term electricity demand forecasting using double seasonal exponential smoothing

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