摘要
网络组织和生长方式多变,现代网络呈拓扑结构复杂化、网络设备异构、信息交互频繁等特征,增加网络态势分析与决策难度,需加强对网络态势感知分析的研究,通过与BP神经网络比较进行深度学习网络态势研究,结果表明,深度学习较BP神经网络在网络态势感知方面有较大优越性。
Due to the flexibility of Network itself organization and growth way, mordem network showed ofcharacteristics of complicated topology, heterogeneous network equipment, and frequent information exchange in the development process, which greatly increased the difficulty of the cyberspace situation analysis and decision-making, it is need to strengthen the analysis of cyberspace situation awareness. By comparison of Deep Learning and BP neural network, the results showed that deep learning had a greater advantage than BP neural network in cyberspace situation awareness.
出处
《东北农业大学学报》
CAS
CSCD
北大核心
2013年第5期144-149,共6页
Journal of Northeast Agricultural University
基金
中央高校基本科研业务费资助项目(HEUCFZ1010
HEUCF100604)
关键词
网络态势感知
深度学习
网络态势
机器学习
cyberspace situation awareness
deep leaming
cyberspace situation
machine leaming
