Journal of Geo-information Science ›› 2023, Vol. 25 ›› Issue (6): 1148-1163.doi: 10.12082/dqxxkx.2023.220967

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Multi-level Knowledge Modeling Method of Battlefield Environment based on Temporal Knowledge Hypergraph Model

JIANG Bingchuan1(), HUANG Zihang1,2, REN Yan1, SUN Yong1, FAN Aimin3   

  1. 1. Institute of Geospatial Information,Strategic Support Force Information Engineering University, Zhengzhou 450001, China
    2. Graduate School, Strategic Support Force Information Engineering University, Zhengzhou 450001, China
    3. PLA 66444 Troops, Beijing 100042, China
  • Received:2022-12-11 Revised:2023-02-28 Online:2023-06-25 Published:2023-06-02
  • Contact: *JIANG Bingchuan, E-mail:
  • Supported by:
    National Natural Science Foundation of China(42171456);National Defense Science and Technology Foundation Strengthening Plan(2021-JCJQ-JJ-0507);National Key R&D Program of China(2022ZD0116404)


The new combat style places new requirements for battlefield environment service support. The intelligent service of battlefield environment urgently needs to improve knowledge based on the global multidimensional battlefield environment data. In view of the knowledge modeling problem of intelligent cognition of battlefield environment, this paper puts forward the classification method of battlefield environment knowledge and considers the battlefield environment knowledge graph as a new form of battlefield environment knowledge representation under the context of big data and artificial intelligence. To solve the fragmentation problem of triplet knowledge representation, a temporal hypergraph representation model of battlefield environment is constructed, a multi-level unified graph model combining entity knowledge, event knowledge, influence process knowledge, and service decision-making knowledge is realized, and all kinds of knowledge are represented as a unified knowledge hypergraph network with spatiotemporal and scene characteristics. Finally, the experimental verification is carried out based on the data of map, event, impact process, and combat impact effectiveness. The hypergraph network realizes the correlation of various battlefield environment knowledge from the semantic level, which can provide support for the further realization of intelligent reasoning and service decision-making based on hypergraph.

Key words: knowledge representation, battlefield environment knowledge graph, knowledge hypergraph, knowledge hyperedge, multi-level temporal knowledge hypergraph model