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Improved BAS-BiLSTM-Attention model for wind power forecasting

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Bibliographic Details
Published in:International Journal of Low-Carbon Technologies
Format: Online Article RSS Article
Published: 2026
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container_title International Journal of Low-Carbon Technologies
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:17154
institution FRELIP
journal_source_facet International Journal of Low-Carbon Technologies
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Improved BAS-BiLSTM-Attention model for wind power forecasting
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Mathematical Sciences
sub_discipline_facet Natural Sciences — Mathematical Sciences
subject_display Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
subject_facet Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
title Improved BAS-BiLSTM-Attention model for wind power forecasting
title_auth Improved BAS-BiLSTM-Attention model for wind power forecasting
title_full Improved BAS-BiLSTM-Attention model for wind power forecasting
title_fullStr Improved BAS-BiLSTM-Attention model for wind power forecasting
title_full_unstemmed Improved BAS-BiLSTM-Attention model for wind power forecasting
title_short Improved BAS-BiLSTM-Attention model for wind power forecasting
title_sort improved bas-bilstm-attention model for wind power forecasting
topic Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
url https://academic.oup.com/ijlct/article/doi/10.1093/ijlct/ctaf146/8487605?rss=1