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		<title>Dalmau Codina et al 2019b - Revision history</title>
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		<updated>2026-05-08T12:50:44Z</updated>
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		<id>https://www.scipedia.com/wd/index.php?title=Dalmau_Codina_et_al_2019b&amp;diff=209323&amp;oldid=prev</id>
		<title>Scipediacontent: Scipediacontent moved page Draft Content 735812376 to Dalmau Codina et al 2019b</title>
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				<updated>2021-02-03T21:03:14Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_735812376&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 735812376&quot;&gt;Draft Content 735812376&lt;/a&gt; to &lt;a href=&quot;/public/Dalmau_Codina_et_al_2019b&quot; title=&quot;Dalmau Codina et al 2019b&quot;&gt;Dalmau Codina et al 2019b&lt;/a&gt;&lt;/p&gt;
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				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 21:03, 3 February 2021&lt;/td&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

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		<id>https://www.scipedia.com/wd/index.php?title=Dalmau_Codina_et_al_2019b&amp;diff=209322&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==  The uncertainty of the take-off time is a major contribution to the loss of trajectory predictability. At present, the Estimated Take-Off Time (ETOT) for each...&quot;</title>
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				<updated>2021-02-03T21:03:11Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==  The uncertainty of the take-off time is a major contribution to the loss of trajectory predictability. At present, the Estimated Take-Off Time (ETOT) for each...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
The uncertainty of the take-off time is a major contribution to the loss of trajectory predictability. At present, the Estimated Take-Off Time (ETOT) for each individual flight is extracted from the Enhanced Traffic Flow Management System (ETFMS) messages, which are sent each time there is an event triggering a recalculation of the flight data by the Network Man- ager Operations Centre. However, aircraft do not always take- off at the ETOTs reported by the ETFMS due to several factors, including congestion and bad weather conditions at the departure airport, reactionary delays and air traffic flow management slot improvements. This paper presents two machine learning models that take into account several of these factors to improve the take- off time prediction of individual flights one hour before their estimated off-block time. Predictions performed by the model trained on three years of historical flight and weather data show a reduction on the take-off time prediction error of about 30% as compared to the ETOTs reported by the ETFMS. Peer Reviewed&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://hdl.handle.net/2117/181173 http://hdl.handle.net/2117/181173] under the license http://creativecommons.org/licenses/by-nc-nd/3.0/es/&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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