Data for: Recycled Aggregate Pervious Concrete: Key Properties Statistics and Prediction Analysis

In this paper, the statistical distribution law of Recycled Aggregate Pervious Concrete (RAPC) properties and its prediction accuracy are analysed. And the relationship model between RAPC properties (horizontal relationship prediction model) and the relationship model between raw materials and RAPC properties (longitudinal relationship prediction model) are established by using the BP neural network method, and the prediction analysis can be carried out by using Python software.

本文针对再生骨料透水混凝土（Recycled Aggregate Pervious Concrete，RAPC）的性能统计分布规律及其预测精度展开分析。采用BP神经网络（Back Propagation Neural Network）方法构建了两类关联模型：其一为RAPC性能间的横向关联预测模型，其二为原材料与RAPC性能间的纵向关联预测模型，且可借助Python软件开展预测分析工作。