{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:34:54Z","timestamp":1772930094295,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Time series forecasting in power systems is crucial for power supply planning and exerts a direct impact on the electricity market. Accurate forecasting can effectively mitigate decision-making risks. This paper proposes a forecasting method based on a multi-dimensional Taylor network (MTN) and applies it to electricity price prediction. The time series is decomposed into one low-frequency signal and several high-frequency signals. The MTN model is constructed for each frequency sequence. The final forecast is obtained by aggregating the predictions from all frequency components. Using European electricity price data as a case study, experimental results demonstrate that the proposed method achieves high predictive accuracy.<\/jats:p>","DOI":"10.3390\/a19030194","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T10:31:14Z","timestamp":1772706674000},"page":"194","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Green Power Price Forecast Based on Multi-Dimensional Taylor Network and Wavelet Method"],"prefix":"10.3390","volume":"19","author":[{"given":"Yaqin","family":"Qiu","sequence":"first","affiliation":[{"name":"School of Intelligent Engineering, Henan Institute of Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Intelligent Engineering, Henan Institute of Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nanyun","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Nanjing Tech University, Nanjing 210086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5010-4903","authenticated-orcid":false,"given":"Qiming","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1008","DOI":"10.1109\/TAC.2024.3449689","article-title":"Feedback Stability Under Mixed Gain and Phase Uncertainty","volume":"70","author":"Liang","year":"2025","journal-title":"IEEE Trans. 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