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Novel Algorithm for Identifying and Fusing Conflicting Data in Wireless Sensor Networks

There is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh P... Full description

Journal Title: Sensors 01 May 2014, Vol.14(6), pp.9562-9581
Main Author: Zhenjiang Zhang
Other Authors: Tonghuan Liu , Dong Chen , Wenyu Zhang
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: E-ISSN: 1424-8220 ; DOI: 10.3390/s140609562
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title: Novel Algorithm for Identifying and Fusing Conflicting Data in Wireless Sensor Networks
format: Article
creator:
  • Zhenjiang Zhang
  • Tonghuan Liu
  • Dong Chen
  • Wenyu Zhang
subjects:
  • Wireless Sensor Network Data Fusion
  • Keyword
  • Ds Theory
  • Evidential Conflict
  • Engineering
ispartof: Sensors, 01 May 2014, Vol.14(6), pp.9562-9581
description: There is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh Paradox, and one-vote veto. These issues lead to a great difference between the fusion results and real results. This paper applies the idea of analyzing distance-based evidence conflicts, introduces the concept of vector space, and proposes a new cosine theorem-based method of identifying and expressing conflicting data. In addition, this paper proposes a new data fusion algorithm based on the degree of mutual support between beliefs, which is based on the Jousselme distance-based combination rule proposed by Deng et al. Simulation results demonstrate that the presented algorithm achieves great improvements in both the accuracy of identifying conflicting data and that of fusing conflicting data.
language: eng
source:
identifier: E-ISSN: 1424-8220 ; DOI: 10.3390/s140609562
fulltext: fulltext_linktorsrc
issn:
  • 1424-8220
  • 14248220
url: Link


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titleNovel Algorithm for Identifying and Fusing Conflicting Data in Wireless Sensor Networks
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subjectWireless Sensor Network Data Fusion ; Keyword ; Ds Theory ; Evidential Conflict ; Engineering
descriptionThere is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh Paradox, and one-vote veto. These issues lead to a great difference between the fusion results and real results. This paper applies the idea of analyzing distance-based evidence conflicts, introduces the concept of vector space, and proposes a new cosine theorem-based method of identifying and expressing conflicting data. In addition, this paper proposes a new data fusion algorithm based on the degree of mutual support between beliefs, which is based on the Jousselme distance-based combination rule proposed by Deng et al. Simulation results demonstrate that the presented algorithm achieves great improvements in both the accuracy of identifying conflicting data and that of fusing conflicting data.
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There is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh Paradox, and one-vote veto. These issues lead to a great difference between the fusion results and real results. This paper applies the idea of analyzing distance-based evidence conflicts, introduces the concept of vector space, and proposes a new cosine theorem-based method of identifying and expressing conflicting data. In addition, this paper proposes a new data fusion algorithm based on the degree of mutual support between beliefs, which is based on the Jousselme distance-based combination rule proposed by Deng et al. Simulation results demonstrate that the presented algorithm achieves great improvements in both the accuracy of identifying conflicting data and that of fusing conflicting data.

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There is continuously increasing interest in research on multi-sensor data fusion technology. Because Dempster’s rule of combination can be problematic when dealing with conflicting data, there are numerous issues that make data fusion a challenging task, including the exponential explosion, Zadeh Paradox, and one-vote veto. These issues lead to a great difference between the fusion results and real results. This paper applies the idea of analyzing distance-based evidence conflicts, introduces the concept of vector space, and proposes a new cosine theorem-based method of identifying and expressing conflicting data. In addition, this paper proposes a new data fusion algorithm based on the degree of mutual support between beliefs, which is based on the Jousselme distance-based combination rule proposed by Deng et al. Simulation results demonstrate that the presented algorithm achieves great improvements in both the accuracy of identifying conflicting data and that of fusing conflicting data.

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