Yuan Kaijuan, Xiao Fuyuan, Fei Liguo, Kang Bingyi, Deng Yong
School of Computer and Information Science, Southwest University, Chongqing, 400715 China.
School of Computer and Information Science, Southwest University, Chongqing, 400715 China ; Institute of Integrated Automation, School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shanxi 710049 China ; School of Engineering, Vanderbilt University, Nashville, TN 37235 USA.
Springerplus. 2016 May 17;5:638. doi: 10.1186/s40064-016-2205-6. eCollection 2016.
Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods.
无线传感器网络在智能导航中发挥着重要作用。它集成了一组传感器,以克服单一检测系统的局限性。Dempster-Shafer证据理论可以通过数据融合来组合无线传感器网络的传感器数据,这有助于提高检测系统的准确性和可靠性。然而,由于传感器的来源不同,在不确定环境下传感器数据之间可能会存在冲突。因此,本文提出了一种结合邓熵和证据距离的新方法来解决这一问题。首先,采用邓熵来度量不确定信息。然后,应用证据距离来度量冲突程度。该新方法能够有效地处理冲突,提高检测系统的准确性和可靠性。通过一个例子说明了新方法的有效性,并将结果与现有方法的结果进行了比较。