Command control network modeling method based on multiple-attribute weighting

Abstract

The invention discloses a command and control network modeling method based on multi-attribute weighting, which belongs to the field of command and control. Specifically: firstly, define the node attributes as accusation ability, node task-related attributes, and spatial distance; secondly, combine the degree and betweenness, comprehensively consider the network attributes of the network local and network global feature expression nodes, and weight them with their own attributes Combined with the design of multi-attribute weighted accusation network edge connection strategy algorithm and implementation method. This method can effectively be close to the real situation of the battlefield, follow the power law distribution, and have high combat efficiency, which can provide a theoretical basis for the network construction of the command and control system.

Description

technical field [0001] The invention belongs to the command and control field, in particular to a command and control network modeling method based on multi-attribute weighting. Background technique [0002] The command and control network under the condition of informatization is a network structure composed of various nonlinear logical interaction relationships based on the physical communication network. The description of the relationship between them and the modeling of the accusation network put forward higher requirements. [0003] The research on accusation network modeling mainly includes: empirical analysis of accusation network complexity, accusation network model description and model evolution. Through the modeling of the accusation network, the edge connection relationship of the accusation network is established. The connection of nodes in the network has its own attributes. The study of network attributes and the attributes of nodes provide an important bas...

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Problems solved by technology

Zhang Qiang et al. established a network description model based on the static subordination connection and dynamic interactive connection of the accusation network. The network edge connection strategy considers the attributes of the nodes themselves and the network attributes, but the network attributes only consider the node degree. The existence of this strategy can only reflect the local information of the network. , it is difficult to reflect the contribution of nodes with low degree but great influence on the network

The edge connection strategy of the accusation network model proposed by Wang Yunming et al. considers the attributes of the nodes themselves and the network attributes, but the network attributes only consider the betweenness to represent the load capacity, ignoring the shortcomings brought by the edge expansion in the model, and it is difficult to reflect the local characteristics of the accusation network.

[0005] The existing edge connection methods in the accusation-based network model can only reflect the importance of local network nodes, and only focus on network connectivity, which is difficult to reflect the local characteristics of the network. Most of the network edge connection strategies in the accusation network model consider the nodes themselves attribute and network attribute, but the network attribute only considers the node degree. This strategy can only reflect the local information of the network, and it is difficult to reflect the contribution of nodes with a low degree but a great influence on the network. The network attribute only considers the betweenness to represent the load. ability, ignoring the shortcomings brought about by edge expansion in the model, it is difficult to reflect the local characteristics of the accusation network, and at the same time, the edge connection strategy takes into account the influence of the local and global characteristics of the network on the importance of nodes, but lacks further simulation analysis and cannot be true and accurate Describe the structural properties of the accusation network

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