Causative Factors Optimization Using Artificial Neural Network for GIS-based Landslide Susceptibility Assessments in Ambon, Indonesia.
Author:
Affiliation:
1. Forest Environment Science Department, Kyushu University
2. Faculty of Agriculture, Kyushu University
Publisher
Japan Society of Erosion Control Engineering
Link
https://www.jstage.jst.go.jp/article/ijece/10/3/10_120/_pdf
Reference16 articles.
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2. Carvalho, L. F. et al. (2014): Digital signature of network segment for healthcare environments support. Irbm, Vol. 35, No. 6, pp. 299-309.
3. Cilliers, P. (1998): Complexity and postmodernism: Understanding complex systems. South African Journal of Philosopy, Vol. 18, No. 2, pp. 258-274.
4. Clerici, A. et al. (2002): A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology, Vol. 48, No. 4, pp. 349-364.
5. Dai, F. C., Lee, C. F. & Ngai, Y. Y. (2002): Landslide risk assessment and management: An overview. Engineering Geology, Vol. 64, No. 1, pp. 65-87.
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