Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 14, 2025

Combined landslide displacement prediction model based on multi-strategy fusion and improved optimization

View Full Paper
Ask AI
Bookmark
Share

Authors

YJYuanfa JiZLZijun LinXSXiyan Sun

Discussion

Loading...

Member takes

Overview

Combined landslide prediction model reduces RMSE by 82% in accuracy, suggesting enhanced forecasting methods.

Key Points

  • MAIN FINDING: The combined prediction model significantly improves landslide displacement forecasting accuracy.
  • KEY EVIDENCE: RMSE reductions of 82% and 52% compared to conventional and single decomposition models demonstrate superior performance.
  • APPROACH: An improved optimization model integrates multiple strategies and optimizes input variables for better accuracy.
  • SIGNIFICANCE: This innovative framework advances landslide prediction, critical for early-warning and risk mitigation in affected areas.

Cite This Study

Ji et al. (2025) studied this question.

synapsesocial.com/papers/689a02afe6551bb0af8cc0f7https://doi.org/10.21203/rs.3.rs-6963877/v1
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Hybrid Landslide Displacement Prediction via Improved Optimization2026 · 2 citations
  2. 2Study on Landslide Displacement Prediction Considering Inducement under Composite Model Optimization2024 · 9 citations
  3. 3A dynamic prediction model of landslide displacement based on VMD–SSO–LSTM approach2024 · 30 citations
  4. 4A unified deep learning framework coupling InSAR-derived spatiotemporal kinematic features for robust landslide displacement prediction2026
  5. 5Dynamic prediction model of landslide displacement based on (SSA-VMD)-(CNN-BiLSTM-attention): a case study2024 · 5 citations