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Identification of the Optimal Parameters for Forecasting the State of Technical Objects Based on the Canonical Random Sequence Decomposition.

Igor P. AtamanyukVyacheslav ShebaninYuriy P. KondratenkoValerii HavryshVadim LykhachSergey Kramarenko
Published in: DESSERT (2020)
Keyphrases
  • optimal parameters
  • support vector regression
  • parameter values
  • genetic algorithm
  • neural network
  • pattern recognition
  • d objects
  • probabilistic model
  • state space