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An Optimized Deep Learning Approach for Improving Airline Services

Shimaa Ouf*

Faculty of Commerce and Business Administration, Business Information Systems Department, Helwan University, Cairo, Egypt

* Corresponding Author: Shimaa Ouf. Email: email

Computers, Materials & Continua 2023, 75(1), 1213-1233. https://doi.org/10.32604/cmc.2023.034399

Abstract

The aviation industry is one of the most competitive markets. The most common approach for airline service providers is to improve passenger satisfaction. Passenger satisfaction in the aviation industry occurs when passengers’ expectations are met during flights. Airline service quality is critical in attracting new passengers and retaining existing ones. It is crucial to identify passengers’ pain points and enhance their satisfaction with the services offered. The airlines used a variety of techniques to improve service quality. They used data analysis approaches to analyze the passenger point data. These solutions have focused simply on surveys; consequently, deep-learning approaches have received insufficient attention. In this study, deep neural networks with the adaptive moment estimation Adam optimization algorithm were applied to enhance classification performance. In previous studies, the quality of the dataset has been ignored. The proposed approach was applied to the airline passenger satisfaction dataset from the Kaggle repository. It was validated by applying artificial neural networks (ANNs), random forests, and support vector machine techniques to the same dataset. It was compared with other research papers that used the same dataset and had a similar problem. The experimental results showed that the proposed approach outperformed previous studies. It has achieved an accuracy of 99.3%.

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Cite This Article

APA Style
Ouf, S. (2023). An optimized deep learning approach for improving airline services. Computers, Materials & Continua, 75(1), 1213-1233. https://doi.org/10.32604/cmc.2023.034399
Vancouver Style
Ouf S. An optimized deep learning approach for improving airline services. Comput Mater Contin. 2023;75(1):1213-1233 https://doi.org/10.32604/cmc.2023.034399
IEEE Style
S. Ouf, "An Optimized Deep Learning Approach for Improving Airline Services," Comput. Mater. Contin., vol. 75, no. 1, pp. 1213-1233. 2023. https://doi.org/10.32604/cmc.2023.034399



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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