首页|Researchers’ from Lanzhou Jiaotong University Report Details of New Studies and Findings in the Area of Support Vector Machines (Landslide hazard assessment based on improved Stacking model)
Researchers’ from Lanzhou Jiaotong University Report Details of New Studies and Findings in the Area of Support Vector Machines (Landslide hazard assessment based on improved Stacking model)
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NETL
NSTL
Tamkang Univ
Current study results on have been published. According to news reporting from Lanzhou, People’s Republic of China, by NewsRx journalists, research stated, “The early warning of landslides is crucial in mitigating the losses caused by frequent and abrupt landslide disasters along the railway.” Our news editors obtained a quote from the research from Lanzhou Jiaotong University: “The scientific construction of an evaluation model is pivotal in conducting a comprehensive landslide hazard assessment. Using a railway section in Ya’an City as a case study, an improved Stacking model was developed to assess landslide hazard by selecting eight evaluation factors and employing support vector machines, random forests, K-neighborhood, and naive Bayesian learning. Logical regression was utilized as a meta learning tool to evaluate the model’s performance. To address the issue of a limited number of input samples for the meta learner, the proposed approach incorporates reduced dimensionality data from the original dataset as input for the meta learner. This is based on the output of the base learner, resulting in the establishment of an improved Stacking model. The ROC curve is used to verify the accuracy of the model, compare the accuracy of the Stacking model and the single model before and after the improvement, and generate the risk zoning map of the study area.”
NETL
NSTL
Tamkang Univ
