Intelligent Monitoring System for Highway Roadbed Based on Combination Neural Network Algorithm

Abstract

To solve the problem of the frequent occurrence of roadbed faults, we studied the highway roadbed intelligent monitoring system based on a combined neural network algorithm. Based on the embedded system, with a variety of sensors, we completed the construction of the roadbed monitoring system. In the selection of the data processing algorithm model, the combined neural network algorithm based on an artificial immune algorithm and probabilistic neural network (PNN) is selected. The accurate acquisition of data characteristics is realized by data preprocessing, data smoothing and data fitting. Through experimental verification, the accuracy of the research model in identifying roadbed settlements has been improved by about 5% compared to traditional models. Furthermore, the processing time of the model has been shortened by about 19.5%, proving the effectiveness of the model. In terms of fault identification, compared with other classic models, the final recognition accuracy of this model reached 96.7%, far exceeding the comparison model. This provides new ideas for the monitoring and protection of roadbed faults.