Conference Proceedings - World Mining Congress 2026

398 Moore, I. D., Grayson, R. B., & Ladson, A. R. (1991). Digital terrain modelling: A review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5(1), 3–30. https://doi.org/10.1002/hyp.3360050103 Puente-Sotomayor, F., Egas, A., & Teller, J. (2021). Land policies for landslide risk reduction in Andean cities. Habitat International, 107, 102298. Riedmiller, M. (1994). Advanced supervised learning in multi-layer perceptrons—from backpropagation to adaptive learning algorithms. Computer Standards & Interfaces, 16(3), 265–278. Rosi, A., Frodella, W., Nocentini, N., Caleca, F., Havenith, H. B., Strom, A., Saidov, M., Bimurzaev, G. A., & Tofani, V. (2023). Comprehensive landslide susceptibility map of Central Asia. Natural Hazards and Earth System Sciences, 23(6), 2229–2250. Rosales-Huamani, J. A., Perez-Alvarado, R. S., Rojas-Villanueva, U., & Castillo-Sequera, J. L. (2020). Design of a predictive model of rock breakage by blasting using artificial neural networks. Symmetry, 12(9), 1405. Shahri, A. A., Spross, J., Johansson, F., & Larsson, S. (2019). Landslide susceptibility hazard map in southwest Sweden using artificial neural network. Catena, 183, 104225. Turcotte, D. L. (1997). Fractals and chaos in geology and geophysics (2nd ed.). Springer. https://doi.org/10.1007/978-1-4899-1397-5 Vílchez Mata, M. S., & Medina Allcca, L. (2008). Susceptibilidad a los movimientos en masa en las áreas de Chachapoyas y Luya–Amazonas–Perú: Aplicación del método bivariante. XIV Congreso Peruano de Geología. Villacorta, S., Fidel, L., & Zavala Carrión, B. (2012). Mapa de susceptibilidad por movimientos en masa del Perú. Revista de la Asociación Geológica Argentina, 69(3), 393–399. Zhu, Y., Sun, D., Wen, H., Zhang, Q., Ji, Q., Li, C., Zhou, P., & Zhang, J. (2024). Considering the effect of non-landslide sample selection on landslide susceptibility assessment. Geomatics, Natural Hazards and Risk, 15, 2392778.

RkJQdWJsaXNoZXIy MTM0Mzk2