The application of the genetic adaptive neural network in landslide disaster assessment

Jing-Wen Chen, Yung Sheng Chue, Yie Ruey Chen

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

This study applied the Genetic Adaptive Neural Network (GANN) structure to satellite image classification and the assessment of landslide disaster. First, the study conducted quantitative analysis of the various factors of slope development and natural environmental hazards in some parts of the catchment areas of the Laonong River in Southern Taiwan. Meanwhile, using the weighting ratios of various disaster causing factors inferred from the best structure of GANN, this study explored the degree of slope land disturbance. Then, this study incorporated the relationship between rainfall and landslides to draw a landslide potential map using the discriminant analysis approach combined with the GIS platform. The findings of this research will be a valuable reference in thefollow-up drafting of slope development and treatment policies, and the academic and engineering assessment of landslide disasters caused by slope development.

Original languageEnglish
Pages (from-to)442-452
Number of pages11
JournalJournal of Marine Science and Technology (Taiwan)
Volume21
Issue number4
DOIs
Publication statusPublished - 2013 Oct 31

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Ocean Engineering
  • Mechanics of Materials
  • Mechanical Engineering

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