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Design of a Multi-Layered Neural Network Using Particle Swarm Optimization

  • Neural Network
  • Evolutionary Computation
  • Learning
  • Particle Swarm Optimization
  • Meta Heuristics
  • ニューラルネットワーク
  • 進化計算
  • 学習
  • Pso
  • メタヒューリスティク
  • Ndc:370
  • Computer Science


Particle Swarm Optimization (PSO), whose concept has been established as a simulation of a simplified social milieu, is known as one of the most useful optimization methods for solving non-convex continuous optimization problems. This paper describes a new learning algorithm to simultaneously adjust connection weights included in neural networks and some user-specified parameters included in units. According to the proposed algorithm, it is possible to improve the learning properties of the neural networks, e.g., the learning cost and/or adaptability. The behavior of the proposed algorithm is examined on a numerical simulation example.

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