The corrosion resistance of concrete under different strength levels and different corrosion environments was analyzed by using grey relational degree method.The neural network is used to train the concrete corrosion resistance test data,and to predict and verify the data that is not involved in the training.The results show that sand,cement,gravel and anti-corrosion coating have the highest correlation with corrosion resistance,while the other factors have relatively little effect on corrosion resistance.The error between the corrosion resistance parameters predicted by BP neural network and those measured by experiment is basically less than 10%,which can basically meet the requirements.The test and prediction results can provide reference for the prediction of compressive strength of concrete under different strength grades and different corrosion environments in saline soil area.
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