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    <responseDate>2026-10-10T21:07:47Z</responseDate>
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    <identifier>10.57760/sciencedb.space.03235</identifier>
    <datestamp>2026-01-21T17:37:38Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-01-21</dc:date>
  <dc:title>The dataset of fast forward interplanetary shocks observed by the Wind satellite at 1 AU during 1995&amp;ndash;2019</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.space.03235</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset is derived from the interplanetary shock data observed by the Wind satellite at 1AU from 1995 to 2019, which is mainly used to identify fast forward interplanetary shocks (FFs). According to the design of the neural network, the dataset is divided into four categories: FF upstream samples, FF samples, FF downstream samples, and non-FF samples. The number and proportion of each category are distributed as follows: 5280 FF upstream samples (25.13%), 5111 FF samples (24.33%), 5290 FF downstream samples (25.18%), and 5326 non-FF samples (25.35%).&amp;nbsp;</dc:description>
  <dc:subject>shock; solar wind; machine learning</dc:subject>
  <dc:creator>谭燚</dc:creator>
  <dc:creator>周梓露</dc:creator>
  <dc:creator>杨易</dc:creator>
  <dc:creator>沈芳</dc:creator>
  <dc:creator>徐晓军</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-sa/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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