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    <identifier>10.57760/sciencedb.20953</identifier>
    <datestamp>2025-04-03T09:54:35Z</datestamp>
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  <dc:date>2025-04-03</dc:date>
  <dc:title>Parameter-aware Reservoir Computing</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.20953</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>We use the parameter-aware RC method to predict the time series, return map, and bifurcation diagram of the Logistic map. We also use the same method to predict the time series, phase diagram, and bifurcation diagram of the Chua circuit. In addition, we apply the RC method to predict the bifurcation diagram of the Lorenz 96 system, a higher-dimensional chaotic system. We demonstrate that for Reservoirs of the same size with the same system, after training with the same method, the prediction accuracy is affected by the number and position of the bifurcation parameters in the training set.</dc:description>
  <dc:subject>Logistic map; Chua circuit; Lorenz 96 system</dc:subject>
  <dc:creator>Guo jianmin</dc:creator>
  <dc:creator>Du yao</dc:creator>
  <dc:creator>Wang xingang</dc:creator>
  <dc:creator>Yu yizhen</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://api.github.com/licenses/bsd-3-clause</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1088/1674-1056/adb733</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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