Factorial study on airport delay for flight scheduling process
This paper presents the study on the contributing factors of airport delay based on the parametersdecided during flight scheduling process. It is believed that the timing of the scheduled departure will have asignificant impact on the level of airport delays that could be anticipated for the flight....
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my.upm.eprints.234812016-02-03T07:31:52Z http://psasir.upm.edu.my/id/eprint/23481/ Factorial study on airport delay for flight scheduling process Romli, Fairuz Izzudin Tan, Kai Jun Teong, Chee Khoon Ong, Thiam Chun Koo, Teck Hock This paper presents the study on the contributing factors of airport delay based on the parametersdecided during flight scheduling process. It is believed that the timing of the scheduled departure will have asignificant impact on the level of airport delays that could be anticipated for the flight. Three major airportsin the United States: Atlanta’s Hartsfield-Jackson (ATL), New York’s John F. Kennedy (JFK) and also SanFrancisco International Airport (SFO) have been selected as the example case studies. Overall, the ANOVAresults show that scheduling parameters: “day”, “month” and “departure time” significantly affect the airportdelay and should be included in the prediction model. 2012 Conference or Workshop Item NonPeerReviewed Romli, Fairuz Izzudin and Tan, Kai Jun and Teong, Chee Khoon and Ong, Thiam Chun and Koo, Teck Hock (2012) Factorial study on airport delay for flight scheduling process. In: 2012 International Conference on Economics, Business Innovation, 5-6 May 2012, Kuala Lumpur, Malaysia. (pp. 180-184). |
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This paper presents the study on the contributing factors of airport delay based on the parametersdecided during flight scheduling process. It is believed that the timing of the scheduled departure will have asignificant impact on the level of airport delays that could be anticipated for the flight. Three major airportsin the United States: Atlanta’s Hartsfield-Jackson (ATL), New York’s John F. Kennedy (JFK) and also SanFrancisco International Airport (SFO) have been selected as the example case studies. Overall, the ANOVAresults show that scheduling parameters: “day”, “month” and “departure time” significantly affect the airportdelay and should be included in the prediction model. |
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Conference or Workshop Item |
author |
Romli, Fairuz Izzudin Tan, Kai Jun Teong, Chee Khoon Ong, Thiam Chun Koo, Teck Hock |
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Romli, Fairuz Izzudin Tan, Kai Jun Teong, Chee Khoon Ong, Thiam Chun Koo, Teck Hock Factorial study on airport delay for flight scheduling process |
author_facet |
Romli, Fairuz Izzudin Tan, Kai Jun Teong, Chee Khoon Ong, Thiam Chun Koo, Teck Hock |
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Romli, Fairuz Izzudin |
title |
Factorial study on airport delay for flight scheduling process |
title_short |
Factorial study on airport delay for flight scheduling process |
title_full |
Factorial study on airport delay for flight scheduling process |
title_fullStr |
Factorial study on airport delay for flight scheduling process |
title_full_unstemmed |
Factorial study on airport delay for flight scheduling process |
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factorial study on airport delay for flight scheduling process |
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2012 |
url |
http://psasir.upm.edu.my/id/eprint/23481/ |
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