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Review of a Fuzzy Logic Based Airport Passenger Flow Prediction System

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Fuzzy Information Processing 2023 (NAFIPS 2023)

Abstract

We have developed a system that predicts accurately the flow of passengers arriving at the airport a week in advance. The algorithm used by the system leverages Fuzzy Logic for the data processing. The system has been integrated in the Cincinnati/Northern Kentucky International Airport (CVG). This paper is a review of this technology and discusses some of the implicit benefits of its usage.

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References

  1. Monmousseau, P., Jarry, G., Bertosio, F., Delahaye, D., Houalla, M.: Predicting passenger flow at Charles de Gaulle airport security checkpoints.Ā In: 2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation (AIDA-AT), Singapore, 2020, pp. 1ā€“9. IEEE (2020)

    Google ScholarĀ 

  2. Chen, J., Li, J.: Airport passenger flow forecast based on the wavelet neural network model. In: Proceedings of the 2018 2nd International Conference on Deep Learning Technologies (ICDLT 2018). Association for Computing Machinery, New York, NY, USA (2018)

    Google ScholarĀ 

  3. Liu, L., Chen, R.-C.: A novel passenger flow prediction model using deep learning methods. Transp. Res. Part C: Emerg. Technol. 84, 74ā€“91 (2017)

    ArticleĀ  Google ScholarĀ 

  4. Li, Z., Bil, J., Li, Z.: Passenger flow forecasting research for airport terminal based on SARIMA time series model. In: IOP Conference Series: Earth and Environmental Science, vol. 100, 1st International Global on Renewable Energy and Development (IGRED 2017). IOP Publishing Ltd., Singapore (2017)

    Google ScholarĀ 

  5. Guo, X., Grushka-Cockayne, Y., De Reyck, B.: Forecasting airport transfer passenger flow using real-time data and machine learning. Manuf. Serv. Oper. Manag. 24(6), 3193ā€“3214 (2021)

    ArticleĀ  Google ScholarĀ 

  6. ViaƱa, J., Cohen, K., Saunders, S., Marx, N., Cobb, B.: Explainable algorithm to predict passenger flow at CVG airport. Transportation Research Record (Accepted, to appear)

    Google ScholarĀ 

  7. ViaƱa, J., Cohen, K., Saunders, S., Marx, N., Cobb, B.: ACRP graduate research award: explainable algorithm for passenger flow prediction at the security checkpoint of CVG Cincinnati/Northern Kentucky International Airport. In: Transportation Research Board 102nd Annual Meeting (TRB 2023), Committee on Airport Terminals and Ground Access (AV050), Washington D.C. (2023)

    Google ScholarĀ 

  8. Holguin, S., ViaƱa, J., Cohen, K., Ralescu, A., Kreinovich, V.: Why sine membership functions. In: Dick, S., Kreinovich, V., Lingras, P. (eds.) Applications of Fuzzy Techniques. NAFIPS 2022. Lecture Notes in Networks and Systems, vol. 500, pp. 83ā€“89. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-16038-7_9

  9. EASE Homepage. https://ease.aero. Accessed 19 Mar 2023

  10. ViaƱa, J., Cohen, K.: Systems and methods for predicting airport passenger flow, United States Patent and Trademark Office. International Publication Number: WO 2023/012939 A1. International Publication Date: 16.02.2023

    Google ScholarĀ 

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Correspondence to Javier ViaƱa .

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Ā© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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ViaƱa, J. et al. (2023). Review of a Fuzzy Logic Based Airport Passenger Flow Prediction System. In: Cohen, K., Ernest, N., Bede, B., Kreinovich, V. (eds) Fuzzy Information Processing 2023. NAFIPS 2023. Lecture Notes in Networks and Systems, vol 751. Springer, Cham. https://doi.org/10.1007/978-3-031-46778-3_22

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