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- W4256103571 abstract "ニューラルネットワークは個々の動作が単純であり，高い並列性を有する演算が可能であるため，大規模な組合せ最適化問題を効率的に解くことができる．一方，進化的計算の研究分野では，実数値の設計変数を最適化するための優れた手法が数多く提案されている．本稿では，第一段階でニューラルネットワークを用いた組合せ最適化によって設計変数の削減を行い，第二段階で進化的計算を用いた実数値の設計変数の最適化を行うことで，大規模最適化問題を効率的に解くアプローチを紹介する．本アプローチは，様々な工学システムの最適化に対して適用できると考えられる．筆者らの最近の研究対象である無線センサネットワークにおける問題を例題として取り上げ，本アプローチの有効性と今後の発展性について議論する．" @default.
- W4256103571 created "2022-05-12" @default.
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- W4256103571 date "2014-01-01" @default.
- W4256103571 modified "2023-09-26" @default.
- W4256103571 title "Solving Large Scale Optimization Problems Using Neural Networks and Evolutionary Computation" @default.
- W4256103571 doi "https://doi.org/10.3902/jnns.21.70" @default.
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