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1. Artificial learning
This section is dedicated to the presentation of artificial learning, and more specifically supervised learning, as used in the applications presented below.
1.1 What is artificial learning?
In fairly general terms, artificial learning by induction consists in finding the most plausible general laws that explain particular phenomena we observe.
Such a learning process therefore involves collecting observations of the phenomenon under study, and extracting a forecasting model that we hope will be sufficiently general to subsequently provide correct forecasts on new instances.
Artificial learning problems can be of various kinds:
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Artificial learning
Application to air sector clustering forecasting
Bibliography
Events
USA/Europe ATM R&D seminar
http://www.atmseminarus.org/
International Conference on Research in Air Transportation
http://icrat.org/icrat/
Websites
IEEE Transactions on Intelligent Transportation Systems
Transportation Research
https://www.journals.elsevier.com
MOOC Statistical Learning (Stanford on-line)
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