Evaluation Method for Effectiveness of Anti-Temporal Sensitive Combat Kill Network Based on Neural Network

The number of time-sensitive targets in modern war is increasing day by day, and anti-time-sensitive combat has gradually become an important new combat style. As a killer application against time-sensitive targets, the anti-temporal sensitive combat kill network has attracted much attention. It is of great significance to carry out the research on the effectiveness evaluation of anti-temporal sensitive combat kill network for the operational application and construction development of anti-temporal sensitive combat kill network. However, as a typical complex network, the evaluation model between effectiveness and indicators is highly nonlinear, and the traditional effectiveness evaluation method based on linear assumption is difficult to work. Aiming at this problem, we try to introduce the neural network model with stronger nonlinear expressive ability into the field of effectiveness evaluation, and propose a neural network-based effectiveness evaluation method for anti-temporal sensitive combat kill network. Firstly, based on the system composition of the anti-temporal sensitive combat kill network, the indicators for evaluating effectiveness were sorted out. Secondly, a neural network-based effectiveness evaluation model of the anti-temporal sensitive combat kill network is designed. Finally, the effectiveness of the evaluation method was verified using simulation data.