An Intelligent Mission Planning Model for the Air Strike Operations against Islands Based on Neural Network and Simulation. (4th January 2022)

• Record Type: Journal Article
• Authors: Song, Zhihua; Zhang, Han; Zhao, Yongmei; Dong, Tao; Zhang, Fa
• Other Names: Ma Lianbo Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2022(2022)
• Publication Date: 2022-01-04
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2022/8172907
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : Mission planning of air strike operations is hard because it has to give instructions to a large number of units during a relatively long period of time in an uncertain environment. If some instruction parameters can be calculated by an intelligent agent, better strategies can be found more quickly. In a specific combat scenario of air strike operations against islands, an intelligent model is proposed to improve the performance and flexibility of mission planning. The proposed intelligent mission planning model is based on rule-based decision and uses a fully connected recurrent neural network to calculate some of the decision parameters. The proposed intelligent mission planning model shows better results as compared to rule-based decision making with randomized parameters, and it performs as good as experts in the test set of the specific combat scenario.