REFERENCES Ahmed, H. M., Adewuyi, S., & Ahmed, H. M. A. (2024). Continuous Cash Flow Modeling for Economic Evaluation and Risk Analysis in Mine Planning Using Monte Carlo Simulation. Journal of King Abdulaziz University: Engineering Sciences, 34(2), 81– 93. https://doi.org/10.4197/eng.34-2.6 Lampe, J. (2015). Triangular Distributions and Correlations. 1–29. Malz, A. M. (n.d.). Value-at-Risk. Mathey, M. (2022). Simulation of production processes and associated costs in mining using the Monte Carlo method. Journal of the Southern African Institute of Mining and Metallurgy, 122(12), 697–703. https://doi.org/10.17159/2411-9717/2079/2022 Mirakovski, D., Krstev, B., Krstev, A., & Petrovski, F. (2009). MINE PROJECT EVALUATION TECHNIQUES [Técnicas de evaluación de proyectos mineros]. Park, S., Jung, D., & Choi, Y. (2023). Prediction of Ore Production in a Limestone Underground Mine by Combining Machine Learning and Discrete Event Simulation Techniques. Minerals, 13(6). https://doi.org/10.3390/min13060830 Sarsoruo, C., Gebo, R., & Anderson, P. K. (2019). Simulating a Lognormal Distribution: A Monte Carlo method. Electronic Journal of Informatics, 1, 73–89. Tabesh, M., Upadhyay, S. P., & Askari-Nasab, H. (2016). Discrete Event Simulation of Truck-Shovel Operations in Open Pit Mines. 1–17. Varela, J. R. (2025). No Title. Simulacion 5.0. https://sites.google.com/view/simulacion5/main Zavala, G., Ariza Flores, V., Santos, R., & Blas Cano, J. (2025). Stochastic Cost Estimation in Transportation Infrastructure Projects Using Monte Carlo Simulation and Correlated Risk Variables. Future Transportation, 5(4), 176. https://doi.org/10.3390/futuretransp5040176
RkJQdWJsaXNoZXIy MTM0Mzk2