The Use of Machine Learning Methods to Determine Risk Zones for Construction Disasters Caused by Wind - A Case Study in Poland

• Autorzy: Laks Ireneusz

Identyfikatory

DOI

10.29227/IM-2024-02-62

Warianty tytułu

PL

Wykorzystanie metod uczenia maszynowego do określania stref ryzyka katastrof budowlanych spowodowanych wiatrem – studium przypadku w Polsce

• Konferencja: 9th World Multidisciplinary Congress on Civil Engineering, Architecture, and Urban Planning - WMCCAU 2024 : 2-6.09.2024
• Języki publikacji: EN

Abstrakty

EN

The increasing availability and use of artificial intelligence (AI) methods and algorithms have led to their widespread use in analyses aimed at identifying the decisive factors that influence the course of a studied phenomenon or process. AI algorithms include a wide range of methods. They can be used together or separately. The article describes the use of two Machine Learning (ML) methods, PCA and k-means, to identify parameters that may increase or decrease the risk of construction disasters caused by strong winds in Poland. The analysis was conducted using a unique dataset on construction disasters in Europe, sourced from the General Office of Construction Supervision in Poland for the period 1995-2019. The occurrence of disasters was categorised by voivodeship and cause, with information provided on the number of people injured. ML analyses were conducted to determine whether land development, population density, and weather factors, such as wind, have an impact on the number of recorded disasters.

PL

Zwiększająca się dostępność i wykorzystanie metod oraz algorytmów sztucznej inteligencji prowadzą do ich szerokiego zastosowania w analizach mających na celu identyfikację czynników decydujących o przebiegu badanego zjawiska lub procesu.

Słowa kluczowe

EN

machine learning; PCA; construction disasters; risk zones

PL

uczenie maszynowe; katastrofy budowlane; ryzyko

• Wydawca: Polskie Towarzystwo Przeróbki Kopalin
• Czasopismo: Inżynieria Mineralna
• Rocznik: 2024
• Tom: Vol. 2, no. 2
• Strony: art. no. 62
• Opis fizyczny: Bibliogr. 17 poz., tab., wykr.

Twórcy

autor

Laks Ireneusz

• Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-623 Poznan, Poland

• https://orcid.org/0000-0003-4078-9600

Bibliografia

• 1. S. Kamolov, "Machine learning methods in civil engineering: A systematic review," in Annals of Mathematics and Computer Science, (AMCS,Publisher, 2024), pp. 181-191. https://doi.org/10.56947/amcs.v21.277.
• 2. Y. Georgiadou, M. Carman, B. Rosman, and R. Soden, "Fairness and accountability of AI in disaster risk management: Opportunities and challenges," in Patterns, edited by Elsevier (Amsterdam, Netherlands, 2021), 2(11), 100363. https://doi.org/10.1016/j.patter.2021.100363.
• 3. C. M. Gevaert, M. Carman, B. Rosman, Y. Georgiadou, and R. Soden, "Fairness and accountability of AI in disaster risk management: Opportunities and challenges," in Patterns, edited by Elsevier (Amsterdam, Netherlands, 2021), pp. 100363. https://doi.org/10.1016/j.patter.2021.100363.
• 4. A. Szymczak-Graczyk, I. Laks, B. Ksit, M. Ratajczak, “Analysis of the Impact of Omitted Accidental Actions and the Method of Land Use on the Number of Construction Disasters (a Case Study of Poland),” in Sustainability, edited by (MDPI, Basel, Switzerland, 2021), pp. 618. https://doi.org/10.3390/su13020618
• 5. M.Sybis, J. Mądrawski, W. Kostrzewski, A. Smoczkiewicz-Wojciechowska, “The Study on Possible Applications of Lightweight Concrete Based on Waste Aggregate in Terms of Compressive Strength and Thermal Insulation Properties,” in Polish Journal Of Environmental Studies, edited by (Publisher Name, Publisher City, 2022), pp. 833-841. doi: 10.15244/pjoes/136269
• 6. M. Sybis, E. Konował, “Influence of Modified Starch Admixtures on Selected Physicochemical Properties of Cement Composites,” in Materials, edited by (MDPI, Basel, Switzerland, 2022), pp. 7604-1 - 7604-13. doi: 10.3390/ma15217604
• 7. M. Sybis, E. Konował, K. Prochaska, “Dextrins as green and biodegradable modifiers of physicochemical properties of cement composites,” in Energies, edited by (MDPI, Basel, Switzerland, 2022), pp. 4115-1 - 4115-19. doi: 10.3390/en15114115
• 8. A. Smoczkiewicz-Wojciechowska, M. Sybis, E. Konował, “Rheological properties of starch-containing cement agents exposed to high temperature during convection or microwave drying,” in Przemysł Chemiczny, edited by (SIGMA-NOT, Warszawa, 2021), pp. 56-60. doi: 10.15199/62.2021.2.5
• 9. A. Szymczak-Graczyk, G. Gajewska, I. Laks, W. Kostrzewski, “Influence of Variable Moisture Conditions on the Value of the Thermal Conductivity of Selected Insulation Materials Used in Passive Buildings,” in Energies, edited by (MDPI, Basel, Switzerland, 2022), pp. 2626. doi: 10.3390/en15072626
• 10. B. Ksit, A. Szymczak-Graczyk, M. Thomas, R. Pilch, “Implementation of the Results of Experimental Studies with the Use of the Sclerometric Method of Plane Elements in Wooden Buildings,” in Energies, edited by (MDPI, Basel, Switzerland, 2022), pp. 6660. doi: 10.3390/en15186660
• 11. B. Radomski, T. Mróz, “Application of the Hybrid MCDM Method for Energy Modernisation of an Existing Public Building—A Case Study,” in Energies, edited by (MDPI, Basel, Switzerland, 2023), pp. 3475. doi: 10.3390/en16083475
• 12. B. Radomski, T. Mróz, “The Methodology for Designing Residential Buildings with a Positive Energy Balance - Case Study,” in Energies, edited by (MDPI, Basel, Switzerland, 2021), pp. 5162. doi: 10.3390/en14165162
• 13. A. Dębicka, K. Olejniczak, B. Radomski, D. Kurz, D. Poddubiecki, “Renewable Energy Investments in Poland: Goals, Socio-Economic Benefits, and Development Directions,” in Energies, edited by (MDPI, Basel, Switzerland, 2024), pp. 2374. doi: 10.3390/en17102374
• 14. M. Sybis, G. Milczarek, A. Modrzejewska-Sikorska, E. Konował, “Synthesis of dextrin-stabilized colloidal silver nanoparticles and their application as modifiers of cement mortar,” in International Journal Of Biological Macromolecules, edited by (Elsevier,Amsterdam, 2017), pp. 165-172. doi: 10.1016/j.ijbiomac.2017.06.011
• 15. M. Sybis, E. Konował, “The effect of cement concrete doping with starch derivatives on its frost resistance,” in Przemysł Chemiczny, edited by (SIGMA-NOT, Warszawa, 2019), pp. 1738-1740. doi: 10.15199/62.2019.11.8
• 16. W. J. Krzanowski, "Principles of Multivariate Analysis: A User’s Perspective," in Classic Physiques, edited by R. B. Hamil (Oxford University Press, Oxford, 2000), pp. 212–213.
• 17. E. Pebesma, “Simple Features for R: Standardized Support for Spatial Vector Data,” in The R Journal, edited by (R NEWS, 2018), pp. 439–446. doi:10.32614/RJ-2018-009.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).