An Improved Robust Principal Component Analysis Model for Anomalies Detection of Subway Passenger Flow

Figure 1

The whole procedure of anomalies detection by the improved RPCA. Decompose the matrix of subway passenger flow into a low-rank matrix and a sparse matrix, filter the sparse matrix decomposed by the improved RPCA, and then acquire the anomaly matrix. Mine the potential laws and discover the possible relations among anomalies through ST-DBSCAN algorithm and statistical analysis.