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

Salinity intrusion poses significant challenges to coastal regions worldwide. Reliable salinity prediction models can provide valuable information to mitigate the impact and influence of salinity intrusion. However, their accuracy relies mainly on the selected input variables and used optimal models. This study employs the Bayesian Model Averaging (BMA) algorithm to evaluate input variable importance and select the most reliable salinity prediction model.