网路通信中漂移数据抗干扰镇定模型分析

Network Communication Anti-Jamming Calm Drift Aata Model Analysis

提出一种基于随机决策树以及自适应门限变换的漂移数据抗干扰镇定模型,把随机决策树融入Hoeffding Bounds不等式检测概念漂移数据并过滤其中的干扰因素,通过自适应门限的抗干扰阀值算法,实时跟踪并抑制相关的干扰因素处理,确保网络通信的顺利运行。实验结果说明,该模型的检测准确率、抗噪性、分类精度都优于传统模型,取得了令人满意的效果。

Based on a random drift data of the decision tree and adaptive threshold transform anti-interference calm model, the random decision tree into Hoeffding Bounds inequality detection concept drift data and filtering the interference factors, through the anti-jamming threshold algorithm of adaptive threshold, real-time tracking and suppress the interference factors related processing, ensure the smooth operation of the network communication. Experimental result shows that the detection accuracy of the model, the noise resistance, classification precision is superior to the traditional model, satisfactory results have been achieved.