Calculation of earthwork volume with Artificial Neural Networks (ANN)

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.