Comparison on landslide nonlinear displacement analysis and prediction with computational intelligence approaches

Volume: 11, Issue: 5, Pages: 889 - 896
Published: Oct 23, 2013
Abstract
Landslide displacement is widely obtained to discover landslide behaviors for purpose of event forecasting. This article aims to present a comparative study on landslide nonlinear displacement analysis and prediction using computational intelligence techniques. Three state-of-art techniques, the support vector machine (SVM), the relevance vector machine (RVM), and the Gaussian process (GP), are comparatively presented briefly for modeling...
Paper Details
Title
Comparison on landslide nonlinear displacement analysis and prediction with computational intelligence approaches
Published Date
Oct 23, 2013
Journal
Volume
11
Issue
5
Pages
889 - 896
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.