Landslide risk zoning using support vector machine algorithm

• Main Authors: Ghiasi V., Pauzi N.I.M., Karimi S., Yousefi M.
• Other Authors: 26535838400
• Format: Article
• Published: Techno-Press 2024
• Subjects: kernel functions; landslide; logistic function; mapping; prediction rate-area diagram; support vector machine; Disasters; Losses; Risk assessment; Support vector machines; Topography; Vectors; Watersheds; Financial loss; Gaussian kernels; Kernel function; Landslide risk zoning; Logistics functions; Natural disasters; Prediction rate-area diagram; Prediction-rates; Support vector machines algorithms; Support vectors machine; Landslides

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk...