Open Access
E3S Web Conf.
Volume 198, 2020
2020 10th Chinese Geosynthetics Conference & International Symposium on Civil Engineering and Geosynthetics (ISCEG 2020)
Article Number 03023
Number of page(s) 4
Section Exploration and Innovation of Construction Engineering Technology
Published online 26 October 2020
  1. F. Wang, “An extreme rainfall-induced landslide susceptibility assessment using autoencoder combined with random forest in Shimane Prefecture , Japan,” Geoenvironmental Disasters, vol. 7, 2020. [CrossRef] [Google Scholar]
  2. L. Li, R. Liu, S. Pirasteh, X. Chen, L. He, and J. Li, “A novel genetic algorithm for optimization of conditioning factors in shallow translational landslides and susceptibility mapping,” Arab. J. Geosci., vol. 10, no. 9, 2017, doi: 10.1007/s12517-017-3002-4. [Google Scholar]
  3. G. L. Bennett, S. R. Miller, J. J. Roering, and D. A. Schmidt, “Landslides, threshold slopes, and the survival of relict terrain in the wake of the Mendocino Triple Junction,” Geology, vol. 44, no. 5, pp. 363–366, 2016, doi: 10.1130/G37530.1. [Google Scholar]
  4. A. Ozdemir and T. Altural, “A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan mountains, SW Turkey,” J. Asian Earth Sci., vol. 64, no. Mar.5, pp. 180–197, 2013, doi: 10.1016/j.jseaes.2012.12.014. [Google Scholar]
  5. M. Zare, H. R. Pourghasemi, M. Vafakhah, and B. Pradhan, “Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: A comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms,” Arab. J. Geosci., vol. 6, no. 8, pp. 2873–2888, 2013, doi: 10.1007/s12517-012-0610-x. [CrossRef] [Google Scholar]
  6. D. Tien Bui, T. A. Tuan, H. Klempe, B. Pradhan, and I. Revhaug, “Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree,” Landslides, vol. 13, no. 2, pp. 361–378, 2016, doi: 10.1007/s10346-015-0557-6. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.