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Calculation of earthwork volume with Artificial Neural Networks (ANN)

Year 2025, Volume: 15 Issue: 3, 677 - 683, 15.09.2025
https://doi.org/10.17714/gumusfenbil.1651806

Abstract

Volume calculations are critical for cost analysis, planning and environmental sustainability in disciplines such as civil engineering, environmental engineering, geodesy and mining. In this study, volume values based on digital elevation models (DEMs) generated by various methods were compared to examine the accuracy of earthwork volume calculations. In the DEM generation process, polynomials and multiquadric interpolation methods, which are traditional methods, and feedforward neural network (FFNN) and radial basis neural network (RBFNN), which are artificial neural network methods, were used. Within the scope of the study, earthwork volume calculations were performed using the DEMs produced by these methods and a detailed evaluation of each method was carried out in terms of accuracy, performance and computation time. The results show that artificial neural network based methods provide good accuracy and consistency compared to conventional methods, especially in complex topographies. These findings provide an important contribution to more accurate cost estimation and better assessment of environmental impacts in earthworks projects.

References

  • Akgul, M., Yurtseven, H., Gulci, S., & Akay, A. E. (2018). Evaluation of UAV-and GNSS-based DEMs for earthwork volume. Arabian Journal for Science and Engineering, 43, 1893-1909.
  • Chambers, D. W. (1989). Estimating pit excavation volume using unequal intervals. Journal of Surveying Engineering, 115(4), 390-401. https://doi.org/10.1061/(ASCE)0733-9453(1989)115:4(390)
  • Chen, C.S. and H.C. Lin, 1991. Estimating pit‐excavation volume using cubic spline volume formula. J. Survey Eng., 117: 51-66.DOI: 10.1061/(ASCE)0733-9453(1991)117:2(51). https://doi.org/10.1061/(ASCE)0733-9453(1991)117:2(51)
  • Easa, S. M. (1988). Estimating pit excavation volume using nonlinear ground profile. Journal of Surveying Engineering, 114(2), 71-83. https://doi.org/10.1061/(ASCE)0733-9453(1988)114:2(71)
  • Easa, S. M. (1998). Smooth surface approximation for computing pit excavation volume. Journal of surveying engineering, 124(3), 125-133. https://doi.org/10.1061/(ASCE)0733-9453(1998)124:3(125)
  • Franke, R. (1979). A critical comparison of some methods for interpolation of scattered data. Monterey, CA: Naval Postgraduate School.
  • Güler, A. (1985). Sayısal arazi modellerinde iki enterpolasyon yöntemi ile denemeler. Harita ve Kadastro Mühendisleri Odası Dergisi, (52-53), 98-118.
  • Hardy, R. L. (1971). Multiquadric equations of topography and other irregular surfaces. Journal of geophysical research, 76(8), 1905-1915. https://doi.org/10.1029/JB076i008p01905
  • Hardy, R., L., (1990). Theory of Aplications of the Multiquadratic-biharmonic Method: 20 Years of Discovery 1968-1988, Computers and Mathematics with Application., 19, 8-9,163-208. https://doi.org/10.1016/0898-1221(90)90272-L
  • Hasegawa, H., Sujaswara, A. A., Kanemoto, T., & Tsubota, K. (2023). Possibilities of using UAV for estimating earthwork volumes during process of repairing a small-scale forest road, case study from Kyoto Prefecture, Japan. Forests, 14(4), 677.
  • Haykin, S. (1999). Neural networks: a comprehensive foundation. Prentice Hall PTR.
  • İnal, C., & Yiğit, C. Ö. (2004). Elipsoidal Yüksekliklerin Ortometrik Yüksekliğe Dönüşümünde Enterpolasyon Yöntemlerinin Kullanılabilirliği. Selçuk Üniversitesi Mühendislik, Bilim Ve Teknoloji Dergisi, 19(1), 73-84.
  • Khalil, R. (2014). Computing pit excavation volume using Multiple Regression Analysis. Int. J. Geomat. Geosci, 5, 43-49.
  • Lee, K., & Lee, W. H. (2022). Earthwork volume calculation, 3D model generation, and comparative evaluation using vertical and high-oblique images acquired by unmanned aerial vehicles. Aerospace, 9(10), 606.
  • Moody, J., & Darken, C. J. (1989). Fast learning in networks of locally-tuned processing units. Neural computation, 1(2), 281-294.https://doi.org/10.1162/neco.1989.1.2.281
  • Mukherji, B. (2012). Estimating 3d volume using finite elements for pit excavation. Journal of Surveying Engineering, 138(2), 85-91. https://doi.org/10.1061/(ASCE)SU.1943-5428.00000
  • Park, J., & Sandberg, I. W. (1991). Universal approximation using radial-basis-function networks. Neural computation, 3(2), 246-257.
  • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1985, September). Learning internal representations by error propagation.
  • Şahin, V., & Yılmaz, H. M. (2021). Hacim hesaplarında insansız hava aracı (İHA) verilerinin kullanılabilirliğinin araştırılması. Türkiye İnsansız Hava Araçları Dergisi, 3(2), 36-48.
  • Ulvi, A. (2018). Analysis of the utility of the unmanned aerial vehicle (UAV) in volume calculation by using photogrammetric techniques. International Journal of Eengineering and Geosciences, 3(2), 43-49.
  • Yakar, M., & Yilmaz, H. M. (2008). Using in volume computing of digital close range photogrammetry. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, B3b.
  • Yanalak, M., & Baykal, O. (2001). Transformation of ellipsoid heights to local leveling heights. Journal of Surveying Engineering, 127(3), 90-103. https://doi.org/10.1061/(ASCE)0733-9453(2001)127:3(90
  • Yanalak, M. (2005). Computing pit excavation volume. Journal of surveying engineering, 131(1), 15-19. https://doi.org/10.1061/(ASCE)0733-9453(2005)131:1(15)
  • Yılmaz, N. (2017). Comparing the volume methods through using digital elevation models created by different interpolation methods. Feb-Fresenius Environmental Bulletin, 4734.

Yapay Sinir Ağları (YSA) ile hafriyat hacim hesabı

Year 2025, Volume: 15 Issue: 3, 677 - 683, 15.09.2025
https://doi.org/10.17714/gumusfenbil.1651806

Abstract

Hacim hesaplamaları, inşaat mühendisliği, çevre mühendisliği, jeodezi, madencilik gibi disiplinlerde maliyet analizi, planlama ve çevresel sürdürülebilirlik için kritik bir öneme sahiptir. Bu çalışmada, hafriyat hacim hesaplamalarının doğruluğunu incelemek amacıyla, çeşitli yöntemlerle üretilen sayısal yükseklik modellerine (SYM) dayalı hacim değerleri karşılaştırılmıştır. SYM oluşturma sürecinde, geleneksel yöntemler olan polinomlar ve multikuadrik enterpolasyon yöntemleri ile yapay sinir ağları yöntemlerinden ileri beslemeli yapay sinir ağı (İBYSA) ve radyal tabanlı yapay sinir ağı (RTYSA) kullanılmıştır. Çalışma kapsamında, bu yöntemlerle üretilen SYM’ler kullanılarak toprak hacim hesaplamaları gerçekleştirilmiş ve her bir yöntemin doğruluk, performans ve hesaplama süresi açısından detaylı bir değerlendirmesi yapılmıştır. Elde edilen sonuçlar, yapay sinir ağı tabanlı yöntemlerin, özellikle karmaşık topoğrafyalarda, geleneksel yöntemlere kıyasla iyi bir doğruluk ve tutarlılık sağladığını ortaya koymuştur. Bu bulgular, hafriyat projelerinde maliyet tahminlerinin daha doğru yapılabilmesi ve çevresel etkilerin daha iyi değerlendirilebilmesi açısından önemli bir katkı sağlamaktadır.

References

  • Akgul, M., Yurtseven, H., Gulci, S., & Akay, A. E. (2018). Evaluation of UAV-and GNSS-based DEMs for earthwork volume. Arabian Journal for Science and Engineering, 43, 1893-1909.
  • Chambers, D. W. (1989). Estimating pit excavation volume using unequal intervals. Journal of Surveying Engineering, 115(4), 390-401. https://doi.org/10.1061/(ASCE)0733-9453(1989)115:4(390)
  • Chen, C.S. and H.C. Lin, 1991. Estimating pit‐excavation volume using cubic spline volume formula. J. Survey Eng., 117: 51-66.DOI: 10.1061/(ASCE)0733-9453(1991)117:2(51). https://doi.org/10.1061/(ASCE)0733-9453(1991)117:2(51)
  • Easa, S. M. (1988). Estimating pit excavation volume using nonlinear ground profile. Journal of Surveying Engineering, 114(2), 71-83. https://doi.org/10.1061/(ASCE)0733-9453(1988)114:2(71)
  • Easa, S. M. (1998). Smooth surface approximation for computing pit excavation volume. Journal of surveying engineering, 124(3), 125-133. https://doi.org/10.1061/(ASCE)0733-9453(1998)124:3(125)
  • Franke, R. (1979). A critical comparison of some methods for interpolation of scattered data. Monterey, CA: Naval Postgraduate School.
  • Güler, A. (1985). Sayısal arazi modellerinde iki enterpolasyon yöntemi ile denemeler. Harita ve Kadastro Mühendisleri Odası Dergisi, (52-53), 98-118.
  • Hardy, R. L. (1971). Multiquadric equations of topography and other irregular surfaces. Journal of geophysical research, 76(8), 1905-1915. https://doi.org/10.1029/JB076i008p01905
  • Hardy, R., L., (1990). Theory of Aplications of the Multiquadratic-biharmonic Method: 20 Years of Discovery 1968-1988, Computers and Mathematics with Application., 19, 8-9,163-208. https://doi.org/10.1016/0898-1221(90)90272-L
  • Hasegawa, H., Sujaswara, A. A., Kanemoto, T., & Tsubota, K. (2023). Possibilities of using UAV for estimating earthwork volumes during process of repairing a small-scale forest road, case study from Kyoto Prefecture, Japan. Forests, 14(4), 677.
  • Haykin, S. (1999). Neural networks: a comprehensive foundation. Prentice Hall PTR.
  • İnal, C., & Yiğit, C. Ö. (2004). Elipsoidal Yüksekliklerin Ortometrik Yüksekliğe Dönüşümünde Enterpolasyon Yöntemlerinin Kullanılabilirliği. Selçuk Üniversitesi Mühendislik, Bilim Ve Teknoloji Dergisi, 19(1), 73-84.
  • Khalil, R. (2014). Computing pit excavation volume using Multiple Regression Analysis. Int. J. Geomat. Geosci, 5, 43-49.
  • Lee, K., & Lee, W. H. (2022). Earthwork volume calculation, 3D model generation, and comparative evaluation using vertical and high-oblique images acquired by unmanned aerial vehicles. Aerospace, 9(10), 606.
  • Moody, J., & Darken, C. J. (1989). Fast learning in networks of locally-tuned processing units. Neural computation, 1(2), 281-294.https://doi.org/10.1162/neco.1989.1.2.281
  • Mukherji, B. (2012). Estimating 3d volume using finite elements for pit excavation. Journal of Surveying Engineering, 138(2), 85-91. https://doi.org/10.1061/(ASCE)SU.1943-5428.00000
  • Park, J., & Sandberg, I. W. (1991). Universal approximation using radial-basis-function networks. Neural computation, 3(2), 246-257.
  • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1985, September). Learning internal representations by error propagation.
  • Şahin, V., & Yılmaz, H. M. (2021). Hacim hesaplarında insansız hava aracı (İHA) verilerinin kullanılabilirliğinin araştırılması. Türkiye İnsansız Hava Araçları Dergisi, 3(2), 36-48.
  • Ulvi, A. (2018). Analysis of the utility of the unmanned aerial vehicle (UAV) in volume calculation by using photogrammetric techniques. International Journal of Eengineering and Geosciences, 3(2), 43-49.
  • Yakar, M., & Yilmaz, H. M. (2008). Using in volume computing of digital close range photogrammetry. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, B3b.
  • Yanalak, M., & Baykal, O. (2001). Transformation of ellipsoid heights to local leveling heights. Journal of Surveying Engineering, 127(3), 90-103. https://doi.org/10.1061/(ASCE)0733-9453(2001)127:3(90
  • Yanalak, M. (2005). Computing pit excavation volume. Journal of surveying engineering, 131(1), 15-19. https://doi.org/10.1061/(ASCE)0733-9453(2005)131:1(15)
  • Yılmaz, N. (2017). Comparing the volume methods through using digital elevation models created by different interpolation methods. Feb-Fresenius Environmental Bulletin, 4734.
There are 24 citations in total.

Details

Primary Language English
Subjects Surveying (Incl. Hydrographic Surveying)
Journal Section Articles
Authors

Leyla Çakır 0000-0001-6624-4727

Nazan Yılmaz 0000-0002-0615-8218

Publication Date September 15, 2025
Submission Date March 5, 2025
Acceptance Date July 4, 2025
Published in Issue Year 2025 Volume: 15 Issue: 3

Cite

APA Çakır, L., & Yılmaz, N. (2025). Calculation of earthwork volume with Artificial Neural Networks (ANN). Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 15(3), 677-683. https://doi.org/10.17714/gumusfenbil.1651806