Compaction Uniformity Evaluation of Subgrade in Highway Based on Principal Components Analysis and Back Propagation Neural Networks

This paper proposes a comprehensive method for the compaction uniformity evaluation of subgrade in highways based on principle components analysis and BP neural network. A field test resilient Young’s moduli during is performed Zun-Qin highway. The representing are key factors principal component analysis, used as input Back Propagation (BP) networks. degree variation synthesis score three sections discussed, results show that has good performance evaluating subgrade. insight from this study provides novel incites better understanding highways.