摘要
在变级配多组试验数据的基础上 ,建立了人工神经网络预测模型。以各筛孔通过率作为输入 ,矿料间隙率和粗骨架间隙率作为输出 ,得到的神经网络预测模型 ,对于某种具体的材料 。
In this paper, the model of prediction using neural network method is provided based on a lot of test data of different gradations. Taking percentage passing sieve opening as input and percent voids in mineral aggregate and percent voids in coarse mineral aggregate as output, this model is set up. It is feasible and efficient for prediction of bulk properties of other gradations with the same asphalt cotent of the specific material.
出处
《长沙交通学院学报》
2002年第4期48-51,共4页
Journal of Changsha Communications University
