COMBINED SBAS-INSAR AND PSO-RF ALGORITHM FOR EVALUATING THE SUSCEPTIBILITY PREDICTION OF LANDSLIDE IN COMPLEX MOUNTAINOUS AREA: A CASE STUDY OF LUDIAN COUNTY, CHINA

Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China

In complex mountainous areas where earthquakes are frequent, landslide hazards pose a significant threat to human life and property due to their high degree of concealment, complex development mechanism, and abrupt nature.In view of the problems of the existing landslide hazard susceptibility evaluation model, such as poor effectiveness and inaccur

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Bet-hedging strategies in expanding populations.

In ecology, species can mitigate their extinction risks in uncertain environments by diversifying individual phenotypes.This observation is quantified by the theory of bet-hedging, which provides a reason for the degree of phenotypic diversity observed even in clonal populations.Bet-hedging in well-mixed populations is rather well understood.Howeve

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