Dynamic Decision-Making Modeling for Army Operation Command Post Entity

Authors

Kang Kai, 1.The Institute of Command Information System in PLA University of Science and Technology, Nanjing 210007, China; ;
Yongliang Zhang, 1.The Institute of Command Information System in PLA University of Science and Technology, Nanjing 210007, China; ;
Chenxi Li, 1.The Institute of Command Information System in PLA University of Science and Technology, Nanjing 210007, China; ;
Jintang Pan, 2.The Troop of 73906 PLA, Nanjing 210007,China;

Abstract

Abstract: The paper presents a modeling method of dynamic decision-making for army operation command post entity based on the Bayesian Net (BN) to meet the demands of demonstrating the operational blue print and evaluating the plan with the support of subject matter experts and military rules. The method brings about the structured description for the decision-making rules, builds the BN model for battlefield situation, and actualizes the situation estimation based on the model of BN reasoning. Therefore it gives the reasonable analysis, the in-depth understanding and right dynamic estimation to the land battlefield dynamic situation, which embodies the complexity and self-adaptability of the joint operation. It provides a better solution to solve the dynamic decision-making modeling problem of the army operation command post entity.

Recommended Citation

Kai, Kang; Zhang, Yongliang; Li, Chenxi; and Pan, Jintang (2019) "Dynamic Decision-Making Modeling for Army Operation Command Post Entity," Journal of System Simulation: Vol. 30: Iss. 2, Article 4.
DOI: 10.16182/j.issn1004731x.joss.201802004
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss2/4

First Page

398

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201802004

Last Page

405

CLC

TP391.9;E211

Recommended Citation

Kang Kai, Zhang Yongliang, Li Chenxi, Pan Jintang. Dynamic Decision-Making Modeling for Army Operation Command Post Entity[J]. Journal of System Simulation, 2018, 30(2): 398-405.

DOI

10.16182/j.issn1004731x.joss.201802004