A spatiotemporal co-occurrence pattern mining algorithm based on ship trajectory data

Abstract

Finding the potential spatiotemporal co-occurrence behavior patterns of large groups of ships while sailing is a challenging problem of great importance in many real-world applications. Through spatiotemporal data mining of ship trajectory data, route rules, navigation behavior, and potential anomalies can be mined, providing important support for maritime management, navigation safety, and emergency response. With the analysis and mining of ship trajectory data in some hotspot sea areas, this paper introduced a ship spatiotemporal co-occurrence pattern mining algorithm based on association rules. Based on the research of data model and the judgment criterion of spatio-temporal co-occurrence law, such concepts as candidate set, frequency set, and instance set are introduced together with the key procedure of algorithm, including pruning and pasting of candidate sets, screening of instance sets, definition of association reasoning, and association rule mining. Subsequently, the process of implementing the spatiotemporal co-occurrence pattern mining algorithm is devised. In the end, the algorithm is verified by taking the automatic identification system data of ships in hotspot sea areas as the source data. The proposed algorithm can find several ship combinations with spatiotemporal co-occurrence regularity in these hotspot sea areas, and the association rules on the co-occurrence of several ships. The performance of the proposed algorithms is illustrated on a real-world ship trajectory database and made a detailed comparative analysis. The results are very promising in terms of computational time. The experimental results show that our algorithm can effectively identify the motion patterns and behavior characteristics of ships, which provides an important reference and support for Marine traffic management, ship safety and Marine environment protection. The research results of this paper are of great significance for improving the efficiency and safety of maritime traffic, and also provide new ideas and methods for further research in related fields.