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Evaluation of Contingent-Level Battlefield Repair Capability Based on Cloud Model
Yonghua ZENG, Haiyan WANG, Tingting WU, Xiaolong WANG, Baicun JIANG, Hengyuan LIANG
Modern Defense Technology    2024, 52 (5): 116-126.   DOI: 10.3969/j.issn.1009-086x.2024.05.013
Abstract62)   HTML2)    PDF (1935KB)(182)       Save

Battlefield damage assessment and repair (BDAR) is a “multiplier” of combat effectiveness in wartime. Aiming at the need of evaluation of battlefield repair capability and task completion effect of repair detachment under battlefield conditions, a cloud-based evaluation model of contingent-level battlefield repair capability is proposed. By analyzing the influencing factors of BDAR capability, the evaluation index system of detachment-level battlefield emergency repair capability is constructed, and the index weight is determined by combination weighting method. Combined with the cloud theory, the BDAR capability of the evaluation group and the emergency repair group under the simulation condition is comprehensively evaluated. In the simulation condition, the equipment emergency repair and rescue operations of five participating teams were evaluated to verify the scientific and feasibility of the method.

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Construction of Radar Fault Cause Knowledge Graph
Yu-xi XIE, Jiang-ping YANG, Zhi-jian SUN, Yi-yuan LI, Xin HU
Modern Defense Technology    2022, 50 (5): 114-121.   DOI: 10.3969/j.issn.1009-086x.2022.05.015
Abstract4042)   HTML174)    PDF (1561KB)(820)       Save

The analysis of radar fault cause text is helpful to locate the fault location, facilitate equipment maintenance and analyze equipment performance. Knowledge extraction, representation and management of radar fault cause text using knowledge graph technology can effectively improve the utilization efficiency of the text, quickly locate the fault location and analyze the equipment performance in time. On the basis of summarizing the characteristics of radar equipment fault cause text, radar equipment fault cause knowledge graph is constructed by a method combines both the scheme layer and the data layer. The scheme layer of the knowledge graph in the top-down style is designed, which defines the knowledge framework, the concept types, and the relationships between the concepts of the knowledge graph. For the text characteristics, the data layer of knowledge map is constructed in the bottom-up style: in order to solve the problems of small sample size and compound words entity recognition, entity naming recognition is carried out by Att-AlBERT-BiGRU-CRF model. The ALBERT-BiGRU-Att model is used for relationship extraction. Experiments show the effectiveness of the above extraction method. Based on the entities and relationship, the knowledge graph of radar fault causes is constructed.

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Research Progress of Electromagnetic Shielding Shelter Technology
Hai-wei GUO, Yuan LI, Sheng-hui MAO
Modern Defense Technology    2022, 50 (4): 17-27.   DOI: 10.3969/j.issn.1009-086x.2022.04.003
Abstract11844)   HTML468)    PDF (830KB)(1530)       Save

This paper briefly describes the principle of electromagnetic shielding, analyzes the current main shelter electromagnetic shielding technology, introduces the progress of shielding shelter structure design and material research, focuses on the research status and related electromagnetic shielding properties of electromagnetic shielding materials for shelter, and looks forward to the future development trend and application of electromagnetic shielding shelter technology.

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