IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i21p8920-d435466.html
   My bibliography  Save this article

Raptor Feeding Characterization and Dynamic System Simulation Applied to Airport Falconry

Author

Listed:
  • José Luis Roca-González

    (Department of Engineering and Applied Technologies, University Centre of Defence at the Spanish Air Force Academy, 30720 Santiago de la Ribera, Spain)

  • Antonio Juan Briones Peñalver

    (Department of Business Economics, Universidad Politécnica de Cartagena, 30201 Cartagena, Spain)

  • Francisco Campuzano-Bolarín

    (Department of Business Economics, Universidad Politécnica de Cartagena, 30201 Cartagena, Spain)

Abstract

Airport falconry is a highly effective technique for reducing wildlife strikes on aircraft, which cause great economic losses. As an example, nowadays, wildlife strikes on aircrafts in the air transport industry are estimated to cost between USD 187 and 937 million in the US and USD 1.2 billion worldwide every year. Moreover, the life-threatening danger that wildlife strikes pose to passengers has prompted security stakeholders to develop countermeasures to prevent wildlife impacts near airport transit zones. The experience acquired from international countermeasure analysis reveals that falconry is the most effective technique to create sustainable wildlife exclusion areas. However, its application in airport environments continues to be regarded as an art rather than a technique; falconers modulate raptors’ behavior by using a trial-and-error system of controlling their hunger to stimulate the need for prey. This paper focuses on a case study where such a decision-making process was designed as a dynamic system applied to feeding planning for raptors that can be used to set an efficient baseline to optimize raptor responses without damaging existing wildlife. The results were validated by comparing the outputs of the model and the falconer’s trial-and-error system, which revealed that the proposed model was 58.15% more precise.

Suggested Citation

  • José Luis Roca-González & Antonio Juan Briones Peñalver & Francisco Campuzano-Bolarín, 2020. "Raptor Feeding Characterization and Dynamic System Simulation Applied to Airport Falconry," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:8920-:d:435466
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/21/8920/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/21/8920/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kim, Sungil & Kim, Heeyoung, 2016. "A new metric of absolute percentage error for intermittent demand forecasts," International Journal of Forecasting, Elsevier, vol. 32(3), pages 669-679.
    2. Hesse, Gayle & Rea, Roy V. & Booth, Annie L., 2010. "Wildlife management practices at western Canadian airports," Journal of Air Transport Management, Elsevier, vol. 16(4), pages 185-190.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hu, Xincheng & Banks, Jonathan & Wu, Linping & Liu, Wei Victor, 2020. "Numerical modeling of a coaxial borehole heat exchanger to exploit geothermal energy from abandoned petroleum wells in Hinton, Alberta," Renewable Energy, Elsevier, vol. 148(C), pages 1110-1123.
    2. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    3. Andrea Petroselli & Jacek Florek & Dariusz Młyński & Leszek Książek & Andrzej Wałęga, 2020. "New Insights on Flood Mapping Procedure: Two Case Studies in Poland," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    4. Jose Manuel Barrera & Alejandro Reina & Alejandro Maté & Juan Carlos Trujillo, 2020. "Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    5. Fu, Qiang & Wang, Nuo & Shen, MingQi & Song, NanQi & Yan, HuaKun, 2016. "A study of the site selection of a civil airport based on the risk of bird strikes: The case of Dalian, China," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 17-30.
    6. Bhatia, Kushagra & Mittal, Rajat & Varanasi, Jyothi & Tripathi, M.M., 2021. "An ensemble approach for electricity price forecasting in markets with renewable energy resources," Utilities Policy, Elsevier, vol. 70(C).
    7. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
    8. Ahmed Gowida & Tamer Moussa & Salaheldin Elkatatny & Abdulwahab Ali, 2019. "A Hybrid Artificial Intelligence Model to Predict the Elastic Behavior of Sandstone Rocks," Sustainability, MDPI, vol. 11(19), pages 1-22, September.
    9. Indy Man Kit Ho & Anthony Weldon & Jason Tze Ho Yong & Candy Tze Tim Lam & Jaime Sampaio, 2023. "Using Machine Learning Algorithms to Pool Data from Meta-Analysis for the Prediction of Countermovement Jump Improvement," IJERPH, MDPI, vol. 20(10), pages 1-15, May.
    10. Lee, Joseph C.Y. & Draxl, Caroline & Berg, Larry K., 2022. "Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework," Renewable Energy, Elsevier, vol. 200(C), pages 457-475.
    11. Gaetano Perone, 2022. "Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 917-940, August.
    12. Mostofi Fatemeh & Toğan Vedat & Başağa Hasan Basri, 2022. "Real-estate price prediction with deep neural network and principal component analysis," Organization, Technology and Management in Construction, Sciendo, vol. 14(1), pages 2741-2759, January.
    13. Dariusz Młyński, 2020. "Analysis of Problems Related to the Calculation of Flood Frequency Using Rainfall-Runoff Models: A Case Study in Poland," Sustainability, MDPI, vol. 12(17), pages 1-17, September.
    14. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    15. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    16. Montero-Sousa, Juan Aurelio & Aláiz-Moretón, Héctor & Quintián, Héctor & González-Ayuso, Tomás & Novais, Paulo & Calvo-Rolle, José Luis, 2020. "Hydrogen consumption prediction of a fuel cell based system with a hybrid intelligent approach," Energy, Elsevier, vol. 205(C).
    17. Tianxiang Zheng & Shaopeng Liu & Zini Chen & Yuhan Qiao & Rob Law, 2020. "Forecasting Daily Room Rates on the Basis of an LSTM Model in Difficult Times of Hong Kong: Evidence from Online Distribution Channels on the Hotel Industry," Sustainability, MDPI, vol. 12(18), pages 1-17, September.
    18. Sojin Park & Nahyun Kwon & Yonghan Ahn, 2019. "Forecasting Repair Schedule for Building Components Based on Case-Based Reasoning and Fuzzy-AHP," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    19. Stuart J. Fairclough & Danielle L. Christian & Pedro F. Saint-Maurice & Paul R. Hibbing & Robert J. Noonan & Greg J. Welk & Philip M. Dixon & Lynne M. Boddy, 2019. "Calibration and Validation of the Youth Activity Profile as a Physical Activity and Sedentary Behaviour Surveillance Tool for English Youth," IJERPH, MDPI, vol. 16(19), pages 1-17, October.
    20. Lydia Simon & Jost Adler, 2022. "Worth the effort? Comparison of different MCMC algorithms for estimating the Pareto/NBD model," Journal of Business Economics, Springer, vol. 92(4), pages 707-733, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:8920-:d:435466. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.