关键词: 态势预测, 神经网络, 卷积神经网络, 复合卷积结构

Abstract: Aiming at the high training complexity of neural network situation prediction model, a situation prediction method based on improved convolution neural network is proposed. Combined with the advantages of depth-wise separable convolution and factorization into smaller convolution, a new model of improved convolution neural network security situation based on composite convolution structure is proposed, and the mapping of situation elements and situation values are realized. The experimental simulation results show that the method obviously reduces the time complexity and the prediction time, improves the prediction accuracy compared with the existing typical prediction methods.

Key words: situation prediction, neural network, convolution neural network, compound convolution structure