Art

J-GLOBAL ID：201802225592344437   Reference number：18A0112337

Causative Factors Optimization Using Artificial Neural Network for GIS-based Landslide Susceptibility Assessments in Ambon, Indonesia.

インドネシア,アンボンにおけるGISを用いた地滑り危険性評価のためのニューラルネットワーク法を用いた事故係数最適化

Author (2)： ADITIAN Aril (Forest Environment Science Department, Kyushu University) ,  KUBOTA Tetsuya (Faculty of Agriculture, Kyushu University)
Material： International Journal of Erosion Control Engineering (Web)  (Int J Eros Control Eng (Web))
Volume： 10  Issue： 3  Page： 120-129(J-STAGE)  Publication year： 2017 
JST Material Number： U0230A  ISSN： 1882-6547  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： Republic of Indonesia ,  geographic information system ,  *landslide ,  *risk assessment ,  *coefficient ,  height ,  tilt angle ,  slope ,  rock structure ,  ground ,  river ,  earthquake fault ,  road network ,  *neural network (biomodel) ,  *optimization ,  geographical distribution ,  failure probability ,  *modification
Semi thesaurus term： アンボン地方 ,  GIS ,  事故係数 ,  Area Under Curve

Author keywords (4)： landslide susceptibility ,  Ambon ,  artificial neural network ,  causative factors optimization

JST classification (2)： Natural disasters  (RA02030M) ,  Network methods  (KA03040X)

Reference (16)：

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• Clerici, A. et al. (2002): A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology, Vol. 48, No. 4, pp. 349-364.
• 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.

Terms in the title (8)： インドネシア ,  GIS ,  地滑り危険性 ,  評価 ,  ニューラルネットワーク ,  事故 ,  係数 ,  最適化