Application of the bayesian model averaging algorithm in evaluating and selecting optimal salinity prediction models

This study employs the Bayesian Model Averaging (BMA) algorithm to evaluate input variable importance and select the most reliable salinity prediction model. Based on an analysis of observed salinity data and climate data extracted from Landsat 8 OLI in the Google Earth Engine platform, the BMA algorithm identifies the significance of critical variables and optimal salinity prediction models.