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    <identifier>10.57760/sciencedb.27858</identifier>
    <datestamp>2025-07-16T16:55:11Z</datestamp>
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  <dc:date>2025-07-16</dc:date>
  <dc:title>Dynamic heuristic phased Double Deep Q Network path planning algorithm based on Gaussian mixed regression in discrete traffic environment</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.27858</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This data is used in the paper: Dynamic heuristic phased Double Deep Q Network path planning algorithm based on Gaussian mixed regression in discrete traffic environment. Among them, SYQ1~3 is the high-resolution remote sensing image data, and env is the toll cost model constructed based on the paper method. Based on these two types of data, four algorithms are used to generate a path from the starting point to the end point.</dc:description>
  <dc:subject>Path planning algorithms; DDQN; Off-road path planning</dc:subject>
  <dc:creator>Ruixin Zhang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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