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    <identifier>10.57760/sciencedb.26383</identifier>
    <datestamp>2025-06-12T11:13:23Z</datestamp>
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  <dc:date>2025-06-12</dc:date>
  <dc:title>Multimodal Feature Analysis Dataset</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.26383</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>To further analyze the impact of multimodal data on forecasting, we tested the effect of 15 different combinations of modal data on carbon emission forecasting performance. The experiments were divided into Group A and Group B. Group A refers to the combination of different modal variables and historical carbon emission data used as input for forecasting. Group B refers to the combination of different modal variables, internal information data (GDP, population, and total energy consumption), and historical carbon emission data used as input for forecasting.</dc:description>
  <dc:subject>Multimodal; Comparative Experiment; Forecast Accuracy</dc:subject>
  <dc:creator>Li Hongmin</dc:creator>
  <dc:creator>Yang Wenhao</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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