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25523

Machine Learning Techniques for analysis of Egyptian Flight Delay

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Last updated: 03 Jan 2025

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Abstract

Flight delay has been the fiendish problem to the world's aviation industry, so there is very important significance to research for computer system predicting flight delay propagation. Extraction of hidden information from large datasets of raw data could be one of the ways for building predictive model. This paper describes the application of classification techniques for analysing the Flight delay pattern in Egypt Airline's Flight dataset.In this work, four decision tree classifiers were evaluated and results show thatthe REPTree have the best accuracy 80.3%with respect to Forest, StumpandJ48.However, four rules based classifiers were compared and results show that PART provides best accuracy amongstudied rule-based classifiers withaccuracy of 83.1%.By analysing runningtime for all classifiers, the current work concluded that REPtree is the most efficient classifier with respect to accuracy and running time. Also,thecurrent work is extended to apply of Apriori association technique to extract some important information about flight delay. Association rules are presented and association technique is evaluated.    

DOI

10.21608/jsrs.2018.25523

Keywords

Airlines, Flight delay, WEKA, Bigdata, Data mining, classification Algorithms, J48, Random Forest, Decision Stump, Ripper rule, Association Rules, Apriori, Confusion matrix

Authors

First Name

hanaa

Last Name

Mohamed

MiddleName

Maher

Affiliation

1Internet Dev.Dept. Manager of IT Sector,EGYPTAIR Holding Cooperation, Cairo, Egypt

Email

hanaa_maher@egyptair.com

City

-

Orcid

-

First Name

Shahinaz

Last Name

Al-Tabbakh

MiddleName

M.

Affiliation

Computer Science Group, Faculty of Women for Sciences, A. and Education, Ain Shames University, Cairo-Egypt.

Email

shahinaz.altabbakh@women.asu.edu.eg

City

-

Orcid

-

First Name

H.

Last Name

El-Zahed

MiddleName

-

Affiliation

Faculty of Women for Sciences, A. and Education, Ain Shames University, Cairo-Egypt.

Email

helzahed@gmail.com

City

-

Orcid

-

Volume

35

Article Issue

part 1

Related Issue

2138

Issue Date

2018-08-01

Receive Date

2019-01-21

Publish Date

2018-08-01

Page Start

390

Page End

399

Print ISSN

2356-8364

Online ISSN

2356-8372

Article File

JSRS_Volume 35_Issue part 1_Pages 390-399.pdf

PDF . 739.7kB

Link

https://jsrs.journals.ekb.eg/article_25523.html

Detail API

https://jsrs.journals.ekb.eg/service?article_code=25523

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5

Type

Original Article

Type Code

656

Publication Type

Journal

Publication Title

Journal of Scientific Research in Science

Publication Link

https://jsrs.journals.ekb.eg/

MainTitle

Machine Learning Techniques for analysis of Egyptian Flight Delay

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Article

Created At

22 Jan 2023