About: The following paper considers pattern recognition-aided optimization of complex and relevant problem related to optical networks. For that problem, we propose a four-step dedicated optimization approach that makes use, among others, of a regression method. The main focus of that study is put on the construction of efficient regression model and its application for the initial optimization problem. We therefore perform extensive experiments using realistic network assumptions and then draw conclusions regarding efficient approach configuration. According to the results, the approach performs best using multi-layer perceptron regressor, whose prediction ability was the highest among all tested methods.   Goto Sponge  NotDistinct  Permalink

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  • The following paper considers pattern recognition-aided optimization of complex and relevant problem related to optical networks. For that problem, we propose a four-step dedicated optimization approach that makes use, among others, of a regression method. The main focus of that study is put on the construction of efficient regression model and its application for the initial optimization problem. We therefore perform extensive experiments using realistic network assumptions and then draw conclusions regarding efficient approach configuration. According to the results, the approach performs best using multi-layer perceptron regressor, whose prediction ability was the highest among all tested methods.
subject
  • Regression analysis
  • Machine learning
  • Pattern recognition
  • Actuarial science
  • Computational fields of study
  • Classification algorithms
  • Design of experiments
  • Estimation theory
  • Mathematical terminology
  • Mathematical and quantitative methods (economics)
  • Mathematical optimization
  • Operations research
  • Formal sciences
  • Independence (probability theory)
  • Artificial neural networks
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