The Prediction of Pervious Concrete Compressive Strength Based on a Convolutional Neural Network
Gaoming Yu,
Senlai Zhu,
Ziru Xiang
Abstract:To overcome limitations inherent in existing mechanical performance prediction models for pervious concrete, including material constraints, limited applicability, and inadequate accuracy, this study employs a deep learning approach to construct a Convolutional Neural Network (CNN) model with three convolutional modules. The primary objective of the model is to precisely predict the 28-day compressive strength of pervious concrete. Eight input variables, encompassing coarse and fine aggregate content, water co… Show more
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