Notice of RetractionImprovement Research of Evidence Theory in Mine Water Inrush Prediction

Xiao Jianyu, Tong Minming, Feng Wei, Guo Xijin
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引用次数: 1

Abstract

Since the highly conflicting evidence could not be combined effectively through D-S evidence theory, a novel D-S data fusion method based on evidence quality is introduced in this paper. The concrete algorithm for the reliability of observer and the measure of quality function value based on observer reliability are proposed. In the data fusion, adopting the measure of evidence quality, the collected data from multi-sensor is assigned to the different weight according to the reliability of observer, and the probability assignment value is correspondingly adjusted. The improved D-S evidence theory, along with combining the highly conflicting evidence, is applied successfully to the prediction of mine water inrush. The experimental results show that the method is effective.
关于矿井突水预测证据理论撤回改进研究的通知
针对D-S证据理论无法有效融合高冲突证据的问题,提出了一种基于证据质量的D-S数据融合方法。提出了观测器可靠性的具体算法和基于观测器可靠性的质量函数值度量。在数据融合中,采用证据质量度量,根据观察者的信度对多传感器采集的数据赋予不同的权重,并对概率赋值值进行相应调整。将改进的D-S证据理论结合高度矛盾的证据,成功地应用于矿井突水预测。实验结果表明,该方法是有效的。
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