Research on predicting the durability of reactive powder concrete based on CNN and OOA-BP
Due to the limitations of raw materials,the durability of reactive powder concrete(RPC)exhibits highly nonlinear behavior,making it difficult to predict.This paper investigates the application of two artificial neural networks in predicting RPC durability.Specifically,the compressive strength of RPC before and after corrosion is predicted and analyzed using Convolutional Neural Network(CNN)and Osprey Optimization Algorithm BP Neural Network(OOA-BP),with corrosion age and corrosion solution concentration as variables.And the prediction validation is performed on the data that did not participate in training.Comparing the predicted results with the experimental results,it is found that both neural networks have good potential for predicting the durability of RPC,and CNN has better flexibility and accuracy.
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