Research and Application of Data Preprocessing of Highway Slope Deformation Monitoring System

To ensure the accuracy and reliability of highway slope monitoring data prediction, original monitoring data of highway slope was taken from Zhouzhi County as the research object. Using the improved unascertained filtering method (IUF) and differential evolution algorithm (DE), a model was built based on DE algorithm to improve the unascertained filtering method (DE - IUF). This model can identify the error of the slope monitoring data sequence. The error value in the monitoring data sequence is eliminated, and the missing data are supplemented by linear interpolation method, then the method was verified by combining with the measured results. The results show that this method can effectively distinguish error and outlier value, and the identification effect is better than the PauTa criterion method, which can improve the accuracy of slope deformation monitoring data preprocessing, and provide a foundation for the safety prediction and early warning research of highway slope.