伪证据识别和处理在噪声数据评估中的应用

Application of False Evidence Identification and Processing Noise Data Assessment

由于自身因素或外界干扰,机场噪声监测设备往往会测得异常数据,使得该监测点对其他监测点的可信度判断出现错误。当将这种伪证据与其他证据进行融合时,使用D-S组合规则可能会得到较差的融合结果,甚至是违背常理的结果。为了抵消伪证据对融合结果造成的影响,论文介绍了一种利用合成规则的聚焦性识别伪证据的方法,并将识别出的伪证据进行处理再融合。实验结果表明该方法能有效的抵消伪证据造成的影响,得到较好的融合效果,并可成功适用于含有大量不确定信息的机场噪声监测数据可信度证据融合中。

Because of inside factors or outside interference ,airport noise monitoring equipments often measure abnormal data so that the monitoring point makes false assessment of the reliability of the other monitoring points .When this kind of false evidence combines with other evidence ,bad results even counterintuitive results are often got using the D-S combination rule .In order to offset the impact on the fusion results generated from false evidence ,a method of identifying false evidence based on synthesis of the combination rule is presented ,and which are combined after processing the false evidence .The ex-perimental results show that this method can effectively counteract the impact of false evidence and get a better combination effect ,and can be applied in evidence combination of airport noise monitoring data reliability containing a lot of uncertain in-formation .