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Using Python to detect EOFDM Precursors within flight data

Flight data analysis to detect features relevant to the continual improvement of safety.

This lesson introduces the European Flight Data Monitoring Forum EOFDM and their list of precursors to in flight events.

Working group B of the forum created a pseudocode guide for detecting the agreed precursors.

Through several worked examples we will examine different ways to implement some of these algorithms in python and enable discussion of the advantages and disadvantages of each approach.

Contributing

We welcome all contributions to improve the lesson! Maintainers will do their best to help you if you have any questions, concerns, or experience any difficulties along the way.

We'd like to ask you to familiarize yourself with our Contribution Guide and have a look at the more detailed guidelines on proper formatting, ways to render the lesson locally, and even how to write new episodes.

Please see the current list of [issues][FIXME] for ideas for contributing to this repository. For making your contribution, we use the GitHub flow, which is nicely explained in the chapter Contributing to a Project in Pro Git by Scott Chacon. Look for the tag good_first_issue. This indicates that the maintainers will welcome a pull request fixing this issue.

Maintainer(s)

Current maintainers of this lesson are

  • Jonathan Pelham

Authors

A list of contributors to the lesson can be found in AUTHORS

Citation

DOI

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