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Semantic Scholar · Article

FDM Machine Learning: An investigation into the utility of neural networks as a predictive analytic tool for go around decision making

Published 2017-01-01 1 author
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Attribution

This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Semantic Scholar.

Abstract

Verbatim from Semantic Scholar. Not paraphrased, not summarized.

The purpose of this research is to investigate the utility of neural networks in modeling decisions using historic aircraft flight data and low error rates with testing data indicate the success of the network in predicting go-around events.

Author

  • J. Bro

Keywords

  • Computer Science
  • Engineering

Citation: J. Bro (2017). FDM Machine Learning: An investigation into the utility of neural networks as a predictive analytic tool for go around decision making. Semantic Scholar ID 664f29ed0f3fc997581688561dbc161246c7b7f9. https://www.semanticscholar.org/paper/664f29ed0f3fc997581688561dbc161246c7b7f9 ↗