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Pragmatic data-driven AI-based approach for exploring the effects of important constructs on flight cancellations in disruptions and infectious diseases Cover

Pragmatic data-driven AI-based approach for exploring the effects of important constructs on flight cancellations in disruptions and infectious diseases

By:  and    
Open Access
|Aug 2026

Figures & Tables

Table 1:

Performance of the Proposed Methods

MethodAccuracyF1 ScoreRecallPrecision
Two-Class Neural Network1.0001.0001.0001.000
Two-Class Decision Forest1.0001.0001.0001.000
Two-Class Locally Deep SVM1.0001.0001.0001.000
Two-Class Logistics Regression1.0001.0001.0001.000
Table 2:

Confusion Matrices of the Proposed Methods

Two Class Neural NetworkTwo Class Decision ForestTwo Class Locally Deep SVMTwo Class Logistic Regression
TrueFalseTrueFalseTrueFalseTrueFalse
PositiveNegativePositiveNegativePositiveNegativePositiveNegative
5491680549168054916805491680
FalseTrueFalseTrueFalseTrueFalseTrue
PositiveNegativePositiveNegativePositiveNegativePositiveNegative
10101010
Figure 1:

Relations of the Cancellation with Factors

DOI: https://doi.org/10.2478/ejthr-2026-0022 | Journal eISSN: 2182-4924 | Journal ISSN: 2182-4916
Language: English
Page range: 280 - 291
Submitted on: Aug 6, 2025
Accepted on: Mar 12, 2026
Published on: Aug 31, 2026
Published by: Polytechnic Institute of Leiria
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2026 Faiza, Khairir Khalil, published by Polytechnic Institute of Leiria
This work is licensed under the Creative Commons Attribution 4.0 License.