Skip to content

Deep quantum inspired neural network with application to aircraft fuel system fault diagnosis

Semantic Scholar · Article (Neurocomputing) · 042bd687349a47d590d5567decfe1aeb3e01301e · Published 2017-05-17 · Neurocomputing · 4 authors

View on Semantic Scholar ↗

Abstract and citation only, verbatim from Semantic Scholar; full text lives there. All credit to the authors and Neurocomputing.

Abstract

The deep quantum inspired neural network (DQINN) which is an improved deep quantum network ( DQN) to solve fault diagnosis for aircraft fuel system and experiments show that DQINn outperforms other three classical algorithms.

Authors

  • Zehai Gao
  • Cunbao Ma
  • D. Song
  • Yang Liu

Keywords

  • Computer Science
  • Engineering
  • Physics

Citation

Zehai Gao, Cunbao Ma, D. Song , et al. (2017). Deep quantum inspired neural network with application to aircraft fuel system fault diagnosis. Neurocomputing. Semantic Scholar ID 042bd687349a47d590d5567decfe1aeb3e01301e. https://doi.org/10.1016/j.neucom.2017.01.032 ↗