IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i16p8831-d610043.html
   My bibliography  Save this article

A Machine Learning Approach to Determine Airport Asphalt Concrete Layer Moduli Using Heavy Weight Deflectometer Data

Author

Listed:
  • Nicola Baldo

    (Polytechnic Department of Engineering and Architecture (DPIA), University of Udine, Via del Cotonificio 114, 33100 Udine, Italy)

  • Matteo Miani

    (Polytechnic Department of Engineering and Architecture (DPIA), University of Udine, Via del Cotonificio 114, 33100 Udine, Italy)

  • Fabio Rondinella

    (Polytechnic Department of Engineering and Architecture (DPIA), University of Udine, Via del Cotonificio 114, 33100 Udine, Italy)

  • Clara Celauro

    (Department of Engineering, University of Palermo, Viale delle Scienze, Ed. 8, 90128 Palermo, Italy)

Abstract

An integrated approach based on machine learning and data augmentation techniques has been developed in order to predict the stiffness modulus of the asphalt concrete layer of an airport runway, from data acquired with a heavy weight deflectometer (HWD). The predictive model relies on a shallow neural network (SNN) trained with the results of a backcalculation, by means of a data augmentation method and can produce estimations of the stiffness modulus even at runway points not yet sampled. The Bayesian regularization algorithm was used for training of the feedforward backpropagation SNN, and a k-fold cross-validation procedure was implemented for a fair performance evaluation. The testing phase result concerning the stiffness modulus prediction was characterized by a coefficient of correlation equal to 0.9864 demonstrating that the proposed neural approach is fully reliable for performance evaluation of airfield pavements or any other paved area. Such a performance prediction model can play a crucial role in airport pavement management systems (APMS), allowing the maintenance budget to be optimized.

Suggested Citation

  • Nicola Baldo & Matteo Miani & Fabio Rondinella & Clara Celauro, 2021. "A Machine Learning Approach to Determine Airport Asphalt Concrete Layer Moduli Using Heavy Weight Deflectometer Data," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:8831-:d:610043
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/16/8831/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/16/8831/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Suleiman Hassan Otuoze & Dexter V. L. Hunt & Ian Jefferson, 2021. "Neural Network Approach to Modelling Transport System Resilience for Major Cities: Case Studies of Lagos and Kano (Nigeria)," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    2. Rita Justo-Silva & Adelino Ferreira & Gerardo Flintsch, 2021. "Review on Machine Learning Techniques for Developing Pavement Performance Prediction Models," Sustainability, MDPI, vol. 13(9), pages 1-27, May.
    3. Yoonsuh Jung, 2018. "Multiple predicting K-fold cross-validation for model selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 197-215, January.
    4. Fabio Carlucci & Andrea Cirà & Paolo Coccorese, 2018. "Measuring and Explaining Airport Efficiency and Sustainability: Evidence from Italy," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    5. Mulian Zheng & Wang Chen & Xiaoyan Ding & Wenwu Zhang & Sixin Yu, 2021. "Comprehensive Life Cycle Environmental Assessment of Preventive Maintenance Techniques for Asphalt Pavement," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    6. Dejan Makovšek & Polona Tominc & Klavdij Logožar, 2012. "A cost performance analysis of transport infrastructure construction in Slovenia," Transportation, Springer, vol. 39(1), pages 197-214, January.
    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. Ahmed Eid & May Salah & Mahmoud Barakat & Matevz Obrecht, 2022. "Airport Sustainability Awareness: A Theoretical Framework," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    2. Jordi Moreno-Gené & Laura Sánchez-Pulido & Eduard Cristobal-Fransi & Natalia Daries, 2018. "The Economic Sustainability of Snow Tourism: The Case of Ski Resorts in Austria, France, and Italy," Sustainability, MDPI, vol. 10(9), pages 1-20, August.
    3. Enrico Mancinelli & Francesco Canestrari & Andrea Graziani & Umberto Rizza & Giorgio Passerini, 2021. "Sustainable Performances of Small to Medium-Sized Airports in the Adriatic Region," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    4. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    5. Yajun Xiong & Hui Tang & Xiaobo Tian, 2022. "Research on Structural Toughness of Railway City Network in Yellow River Basin and Case Study of Zhengzhou 7–20 Rainstorm Disaster," Sustainability, MDPI, vol. 14(19), pages 1-17, September.
    6. Ihsan Issa Ahmad Hosani & Fikri T. Dweiri & Udechukwu Ojiako, 0. "A study of cost overruns in complex multi-stakeholder road projects in the United Arab Emirates," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 0, pages 1-10.
    7. Fragoudaki, Alexandra & Giokas, Dimitrios, 2020. "Airport efficiency in the dawn of privatization: The case of Greece," Journal of Air Transport Management, Elsevier, vol. 86(C).
    8. Pedro Plasencia-Lozano, 2021. "An Ex Ante Analysis of the Planned Transportation Network in the Region of Extremadura (Spain) by Using Physical Parameters," Sustainability, MDPI, vol. 13(11), pages 1-32, May.
    9. Yong Tian & Lili Wan & Bojia Ye & Runze Yin & Dawei Xing, 2019. "Optimization Method for Reducing the Air Pollutant Emission and Aviation Noise of Arrival in Terminal Area," Sustainability, MDPI, vol. 11(17), pages 1-16, August.
    10. Yongrok Choi & Hua Wen & Hyoungsuk Lee & Hang Yang, 2020. "Measuring Operational Performance of Major Chinese Airports Based on SBM-DEA," Sustainability, MDPI, vol. 12(19), pages 1-17, October.
    11. Ricardo Jorge Raimundo & Maria Emilia Baltazar & Sandra P. Cruz, 2023. "Sustainability in the Airports Ecosystem: A Literature Review," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    12. Asghar, Sobia & Tsusaka, Takuji W. & Jourdain, Damien & Saqib, Shahab E. & Sasaki, Nophea, 2022. "Assessing the efficiency of smallholder sugarcane production: The case of Faisalabad, Pakistan," Agricultural Water Management, Elsevier, vol. 269(C).
    13. Dejan Makovšek & Marian Moszoro, 2018. "Risk pricing inefficiency in public–private partnerships," Transport Reviews, Taylor & Francis Journals, vol. 38(3), pages 298-321, May.
    14. Benito, Bernardino & Martínez-Córdoba, Pedro-José & Guillamón, María-Dolores, 2021. "Measurement and determinants of efficiency in the municipal police service," Evaluation and Program Planning, Elsevier, vol. 85(C).
    15. Weizhang Liang & Asli Sari & Guoyan Zhao & Stephen D. McKinnon & Hao Wu, 2020. "Short-term rockburst risk prediction using ensemble learning methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1923-1946, November.
    16. Sergi, S. Bruno & D’Aleo, Vittorio & Arbolino, Roberta & Carlucci, Fabio & Barilla, David & Ioppolo, Giuseppe, 2020. "Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis," Land Use Policy, Elsevier, vol. 99(C).
    17. Ihsan Issa Ahmad Hosani & Fikri T. Dweiri & Udechukwu Ojiako, 2020. "A study of cost overruns in complex multi-stakeholder road projects in the United Arab Emirates," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1250-1259, December.
    18. Jiachuang Wang & Haoji Ma & Xianhang Yan, 2023. "Rockburst Intensity Classification Prediction Based on Multi-Model Ensemble Learning Algorithms," Mathematics, MDPI, vol. 11(4), pages 1-29, February.
    19. Nwaogbe Obioma R. & Omoke Victor & Ayinla Akorede Ibrahim & Ojekunle Joel A. & Wokili-Yakubu Hauwa, 2021. "Analysis of Airport Operational Performance in Selected Airports of Northern Nigeria," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 12(1), pages 111-122, January.
    20. Bilal Asghar & Ahmad Wasim & Usama Qazi & Azfar Rasool, 2020. "Financial and Non-Financial Practices Driving Sustainable Firm Performance: Evidence from Banking Sector of Developing Countries," Sustainability, MDPI, vol. 12(15), pages 1-15, July.

    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:13:y:2021:i:16:p:8831-:d:610043. 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.