A Subgrade Settlement Prediction Model Based on Improved Particle Swarm Neural Network
Bei Quan, Lu Xuanmin · 2020
The research of subgrade settlement prediction has profound value. By monitoring and forecasting, the condition of subgrade can be followed up in time, hidden safety hazards can be found, and preventive measures can be effectively taken to prevent dangerous accidents. At present, the model of subgrade settlement prediction cannot meet the complex and changeable actual situation, so further exploration in this field is of great significance. Based on the traditional BP neural network, this paper improves the particle swarm optimization algorithm in the intelligent optimization algorithm and adds it to the network to construct an effective subgrade settlement prediction model.